The Data Science Course Complete Data Science Bootcamp

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Files Included :

001 A Practical Example What U Will Learn in This Course.mp4 (43.94 MB)
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002 What Does the Course Covers.mp4 (51.36 MB)
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001 Data Science and Business Buzzwords Why are there so Many.mp4 (57.35 MB)
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002 What is the difference between Analysis and Analytics.mp4 (11.16 MB)
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003 Business Analytics, Data Analytics, and Data Science An Introduction.mp4 (52.62 MB)
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004 Continuing with BI, ML, and AI.mp4 (36.95 MB)
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005 A Breakdown of our Data Science Infographic.mp4 (45.3 MB)
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001 The Reason Behind These Disciplines.mp4 (46.7 MB)
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001 Techniques for Working with Traditional Data.mp4 (107.39 MB)
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002 Real Life Examples of Traditional Data.mp4 (18.37 MB)
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003 Techniques for Working with Big Data.mp4 (62.11 MB)
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004 Real Life Examples of Big Data.mp4 (13.07 MB)
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005 Business Intelligence (BI) Techniques.mp4 (52.88 MB)
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006 Real Life Examples of Business Intelligence (BI).mp4 (24.68 MB)
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007 Techniques for Working with Traditional Methods.mp4 (76.1 MB)
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008 Real Life Examples of Traditional Methods.mp4 (27.41 MB)
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009 Machine Learning (ML) Techniques.mp4 (49.41 MB)
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010 Types of Machine Learning.mp4 (80.57 MB)
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011 Real Life Examples of Machine Learning (ML).mp4 (27.7 MB)
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001 Finding the Job - What to Expect and What to Look for.mp4 (13.81 MB)
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001 Debunking Common Misconceptions.mp4 (58.81 MB)
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001 The Basic Probability Formula.mp4 (29.39 MB)
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002 Computing Expected Values.mp4 (45.67 MB)
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003 Frequency.mp4 (37.36 MB)
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004 Events and Their Complements.mp4 (25.83 MB)
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001 Fundamentals of Combinatorics.mp4 (5.95 MB)
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002 Permutations and How to Use Them.mp4 (17.52 MB)
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003 Simple Operations with Factorials.mp4 (16.68 MB)
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004 Solving Variations with Repetition.mp4 (13.95 MB)
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005 Solving Variations without Repetition.mp4 (18.25 MB)
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006 Solving Combinations.mp4 (23.67 MB)
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007 Symmetry of Combinations.mp4 (13.75 MB)
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008 Solving Combinations with Separate Sample Spaces.mp4 (10.65 MB)
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009 Combinatorics in Real-Life The Lottery.mp4 (16.39 MB)
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010 A Recap of Combinatorics.mp4 (15.02 MB)
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011 A Practical Example of Combinatorics.mp4 (42.8 MB)
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001 Sets and Events.mp4 (17.65 MB)
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002 Ways Sets Can Interact.mp4 (19.3 MB)
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003 Intersection of Sets.mp4 (11.01 MB)
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004 Union of Sets.mp4 (24.2 MB)
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005 Mutually Exclusive Sets.mp4 (10.59 MB)
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006 Dependence and Independence of Sets.mp4 (14.92 MB)
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007 The Conditional Probability Formula.mp4 (16.59 MB)
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008 The Law of Total Probability.mp4 (11.59 MB)
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009 The Additive Rule.mp4 (11.11 MB)
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010 The Multiplication Law.mp4 (20.19 MB)
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011 Bayes' Law.mp4 (21.34 MB)
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012 A Practical Example of Bayesian Inference.mp4 (139.14 MB)
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001 Fundamentals of Probability Distributions.mp4 (19.43 MB)
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002 Types of Probability Distributions.mp4 (35.58 MB)
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003 Characteristics of Discrete Distributions.mp4 (9.42 MB)
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004 Discrete Distributions The Uniform Distribution.mp4 (10.31 MB)
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005 Discrete Distributions The Bernoulli Distribution.mp4 (15.12 MB)
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006 Discrete Distributions The Binomial Distribution.mp4 (30.61 MB)
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007 Discrete Distributions The Poisson Distribution.mp4 (23.93 MB)
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008 Characteristics of Continuous Distributions.mp4 (36.13 MB)
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009 Continuous Distributions The Normal Distribution.mp4 (20.01 MB)
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010 Continuous Distributions The Standard Normal Distribution.mp4 (38.36 MB)
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011 Continuous Distributions The Students' T Distribution.mp4 (9.24 MB)
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012 Continuous Distributions The Chi-Squared Distribution.mp4 (20.97 MB)
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013 Continuous Distributions The Exponential Distribution.mp4 (16 MB)
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014 Continuous Distributions The Logistic Distribution.mp4 (16.17 MB)
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015 A Practical Example of Probability Distributions.mp4 (138.12 MB)
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001 Probability in Finance.mp4 (40.34 MB)
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002 Probability in Statistics.mp4 (31.6 MB)
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003 Probability in Data Science.mp4 (56.89 MB)
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001 Population and Sample.mp4 (35.1 MB)
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001 Types of Data.mp4 (43.17 MB)
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002 Levels of Measurement.mp4 (32.18 MB)
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003 Categorical Variables - Visualization Techniques.mp4 (36.64 MB)
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005 Numerical Variables - Frequency Distribution Table.mp4 (17.69 MB)
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007 The Histogram.mp4 (9.57 MB)
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009 Cross Tables and Scatter Plots.mp4 (19.71 MB)
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011 Mean, median and mode.mp4 (24.49 MB)
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013 Skewness.mp4 (13.31 MB)
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015 Variance.mp4 (23.54 MB)
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017 Standard Deviation and Coefficient of Variation.mp4 (20.14 MB)
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019 Covariance.mp4 (18.38 MB)
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021 Correlation Coefficient.mp4 (19.34 MB)
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001 Practical Example Descriptive Statistics.mp4 (150.18 MB)
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001 Introduction.mp4 (3.06 MB)
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002 What is a Distribution.mp4 (17.2 MB)
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003 The Normal Distribution.mp4 (27.49 MB)
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004 The Standard Normal Distribution.mp4 (8.61 MB)
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006 Central Limit Theorem.mp4 (23.22 MB)
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007 Standard error.mp4 (13.52 MB)
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008 Estimators and Estimates.mp4 (27.7 MB)
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001 What are Confidence Intervals.mp4 (28.62 MB)
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002 Confidence Intervals; Population Variance Known; Z-score.mp4 (52.16 MB)
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004 Confidence Interval Clarifications.mp4 (18.94 MB)
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005 Student's T Distribution.mp4 (13.68 MB)
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006 Confidence Intervals; Population Variance Unknown; T-score.mp4 (13.69 MB)
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008 Margin of Error.mp4 (23.1 MB)
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009 Confidence intervals Two means Dependent samples.mp4 (44.97 MB)
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011 Confidence intervals Two means Independent Samples (Part 1).mp4 (11.99 MB)
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013 Confidence intervals Two means Independent Samples (Part 2).mp4 (14.62 MB)
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015 Confidence intervals Two means Independent Samples (Part 3).mp4 (6.89 MB)
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001 Practical Example Inferential Statistics.mp4 (68.98 MB)
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001 Null vs Alternative Hypothesis.mp4 (83.58 MB)
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003 Rejection Region and Significance Level.mp4 (38.69 MB)
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004 Type I Error and Type II Error.mp4 (18.61 MB)
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005 Test for the Mean Population Variance Known.mp4 (36.95 MB)
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007 p-value.mp4 (33.78 MB)
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008 Test for the Mean Population Variance Unknown.mp4 (19.71 MB)
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010 Test for the Mean Dependent Samples.mp4 (32.79 MB)
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012 Test for the mean Independent Samples (Part 1).mp4 (15.41 MB)
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014 Test for the mean Independent Samples (Part 2).mp4 (24.45 MB)
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001 Practical Example Hypothesis Testing.mp4 (45.82 MB)
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001 Introduction to Programming.mp4 (14.76 MB)
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002 Why Python.mp4 (12.04 MB)
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003 Why Jupyter.mp4 (8.13 MB)
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004 Installing Python and Jupyter.mp4 (32.82 MB)
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005 Understanding Jupyter's Interface - the Notebook Dashboard.mp4 (6.07 MB)
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006 Prerequisites for Coding in the Jupyter Notebooks.mp4 (18.96 MB)
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001 Variables.mp4 (8.95 MB)
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002 Numbers and Boolean Values in Python.mp4 (13.7 MB)
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003 Python Strings.mp4 (15.67 MB)
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001 Using Arithmetic Operators in Python.mp4 (8.63 MB)
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002 The Double Equality Sign.mp4 (2.72 MB)
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003 How to Reassign Values.mp4 (1.86 MB)
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004 Add Comments.mp4 (2.41 MB)
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005 Understanding Line Continuation.mp4 (1.2 MB)
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006 Indexing Elements.mp4 (2.36 MB)
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007 Structuring with Indentation.mp4 (2.79 MB)
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001 Comparison Operators.mp4 (4.82 MB)
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002 Logical and Identity Operators.mp4 (19 MB)
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001 The IF Statement.mp4 (6.07 MB)
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002 The ELSE Statement.mp4 (6.04 MB)
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003 The ELIF Statement.mp4 (14.23 MB)
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004 A Note on Boolean Values.mp4 (4.24 MB)
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001 Defining a Function in Python.mp4 (3.23 MB)
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002 How to Create a Function with a Parameter.mp4 (8.33 MB)
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003 Defining a Function in Python - Part II.mp4 (6.45 MB)
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004 How to Use a Function within a Function.mp4 (3.23 MB)
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005 Conditional Statements and Functions.mp4 (5.98 MB)
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006 Functions Containing a Few Arguments.mp4 (2.83 MB)
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007 Built-in Functions in Python.mp4 (10.19 MB)
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001 Lists.mp4 (23.03 MB)
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002 Using Methods.mp4 (30.37 MB)
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003 List Slicing.mp4 (19.18 MB)
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004 Tuples.mp4 (18.19 MB)
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005 Dictionaries.mp4 (32.44 MB)
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001 For Loops.mp4 (23.6 MB)
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002 While Loops and Incrementing.mp4 (20.18 MB)
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003 Lists with the range() Function.mp4 (11.94 MB)
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004 Conditional Statements and Loops.mp4 (21.94 MB)
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005 Conditional Statements, Functions, and Loops.mp4 (4.27 MB)
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006 How to Iterate over Dictionaries.mp4 (16.44 MB)
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001 Object Oriented Programming.mp4 (8.65 MB)
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002 Modules and Packages.mp4 (2.08 MB)
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003 What is the Standard Library.mp4 (5.05 MB)
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004 Importing Modules in Python.mp4 (8.55 MB)
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001 Introduction to Regression Analysis.mp4 (3.59 MB)
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001 The Linear Regression Model.mp4 (13.48 MB)
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002 Correlation vs Regression.mp4 (3.84 MB)
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004 Python Packages Installation.mp4 (23.67 MB)
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005 First Regression in Python.mp4 (29.62 MB)
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007 Using Seaborn for Graphs.mp4 (7.37 MB)
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008 How to Interpret the Regression Table.mp4 (28.73 MB)
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009 Decomposition of Variability.mp4 (8.79 MB)
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010 What is the OLS.mp4 (22.48 MB)
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011 R-Squared.mp4 (11.2 MB)
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001 Multiple Linear Regression.mp4 (5.68 MB)
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002 Adjusted R-Squared.mp4 (34.19 MB)
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004 Test for Significance of the Model (F-Test).mp4 (7.17 MB)
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005 OLS Assumptions.mp4 (5.26 MB)
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006 A1 Linearity.mp4 (3.57 MB)
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007 A2 No Endogeneity.mp4 (9.24 MB)
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008 A3 Normality and Homoscedasticity.mp4 (27.38 MB)
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009 A4 No Autocorrelation.mp4 (7.89 MB)
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010 A5 No Multicollinearity.mp4 (7.6 MB)
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002 How are we Going to Approach this Section.mp4 (5.29 MB)
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003 Simple Linear Regression with sklearn.mp4 (31.62 MB)
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004 Simple Linear Regression with sklearn - A StatsModels-like Summary Table.mp4 (28.89 MB)
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007 Multiple Linear Regression with sklearn.mp4 (11.01 MB)
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008 Calculating the Adjusted R-Squared in sklearn.mp4 (21.75 MB)
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010 Feature Selection (F-regression).mp4 (20.47 MB)
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012 Creating a Summary Table with P-values.mp4 (6.45 MB)
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014 Feature Scaling (Standardization).mp4 (20.36 MB)
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015 Feature Selection through Standardization of Weights.mp4 (24.46 MB)
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016 Predicting with the Standardized Coefficients.mp4 (20.42 MB)
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018 Underfitting and Overfitting.mp4 (5.83 MB)
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019 Train - Test Split Explained.mp4 (35.57 MB)
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001 Practical Example Linear Regression (Part 1).mp4 (84.69 MB)
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002 Practical Example Linear Regression (Part 2).mp4 (31.88 MB)
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004 Practical Example Linear Regression (Part 3).mp4 (16.65 MB)
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006 Practical Example Linear Regression (Part 4).mp4 (39.4 MB)
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008 Practical Example Linear Regression (Part 5).mp4 (50.4 MB)
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001 Introduction to Logistic Regression.mp4 (5.87 MB)
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002 A Simple Example in Python.mp4 (21.89 MB)
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003 Logistic vs Logit Function.mp4 (23.76 MB)
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004 Building a Logistic Regression.mp4 (8.59 MB)
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006 An Invaluable Coding Tip.mp4 (18.76 MB)
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007 Understanding Logistic Regression Tables.mp4 (14.58 MB)
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009 What do the Odds Actually Mean.mp4 (11.39 MB)
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010 Binary Predictors in a Logistic Regression.mp4 (24.83 MB)
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012 Calculating the Accuracy of the Model.mp4 (20.27 MB)
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014 Underfitting and Overfitting.mp4 (7.49 MB)
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015 Testing the Model.mp4 (21.59 MB)
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001 Introduction to Cluster Analysis.mp4 (14.46 MB)
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002 Some Examples of Clusters.mp4 (35.87 MB)
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003 Difference between Classification and Clustering.mp4 (9.67 MB)
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004 Math Prerequisites.mp4 (5.27 MB)
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001 K-Means Clustering.mp4 (10.82 MB)
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002 A Simple Example of Clustering.mp4 (34.21 MB)
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004 Clustering Categorical Data.mp4 (10.35 MB)
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006 How to Choose the Number of Clusters.mp4 (26.87 MB)
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008 Pros and Cons of K-Means Clustering.mp4 (11.12 MB)
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009 To Standardize or not to Standardize.mp4 (10.92 MB)
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010 Relationship between Clustering and Regression.mp4 (3.51 MB)
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011 Market Segmentation with Cluster Analysis (Part 1).mp4 (28.09 MB)
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012 Market Segmentation with Cluster Analysis (Part 2).mp4 (34.09 MB)
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013 How is Clustering Useful.mp4 (37.48 MB)
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001 Types of Clustering.mp4 (9.01 MB)
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002 Dendrogram.mp4 (18.3 MB)
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003 Heatmaps.mp4 (25.71 MB)
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001 What is a Matrix.mp4 (11.94 MB)
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002 Scalars and Vectors.mp4 (8.53 MB)
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003 Linear Algebra and Geometry.mp4 (13.73 MB)
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004 Arrays in Python - A Convenient Way To Represent Matrices.mp4 (18.98 MB)
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005 What is a Tensor.mp4 (15.53 MB)
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006 Addition and Subtraction of Matrices.mp4 (22.1 MB)
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007 Errors when Adding Matrices.mp4 (5.78 MB)
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008 Transpose of a Matrix.mp4 (20.49 MB)
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009 Dot Product.mp4 (12.84 MB)
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010 Dot Product of Matrices.mp4 (34.32 MB)
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011 Why is Linear Algebra Useful.mp4 (88.42 MB)
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001 What to Expect from this Part.mp4 (11.73 MB)
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001 Introduction to Neural Networks.mp4 (10.49 MB)
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002 Training the Model.mp4 (7.71 MB)
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003 Types of Machine Learning.mp4 (13.05 MB)
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004 The Linear Model (Linear Algebraic Version).mp4 (7.98 MB)
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005 The Linear Model with Multiple Inputs.mp4 (7.91 MB)
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006 The Linear model with Multiple Inputs and Multiple Outputs.mp4 (16.66 MB)
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007 Graphical Representation of Simple Neural Networks.mp4 (7.78 MB)
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008 What is the Objective Function.mp4 (6.18 MB)
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009 Common Objective Functions L2-norm Loss.mp4 (5.47 MB)
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010 Common Objective Functions Cross-Entropy Loss.mp4 (9.84 MB)
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011 Optimization Algorithm 1-Parameter Gradient Descent.mp4 (23.59 MB)
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012 Optimization Algorithm n-Parameter Gradient Descent.mp4 (16.83 MB)
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001 Basic NN Example (Part 1).mp4 (9.34 MB)
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002 Basic NN Example (Part 2).mp4 (15.23 MB)
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003 Basic NN Example (Part 3).mp4 (15.65 MB)
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004 Basic NN Example (Part 4).mp4 (39.99 MB)
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001 How to Install TensorFlow 2 0.mp4 (27.32 MB)
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002 TensorFlow Outline and Comparison with Other Libraries.mp4 (15.28 MB)
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003 TensorFlow 1 vs TensorFlow 2.mp4 (15.32 MB)
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004 A Note on TensorFlow 2 Syntax.mp4 (4.63 MB)
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005 Types of File Formats Supporting TensorFlow.mp4 (8.86 MB)
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006 Outlining the Model with TensorFlow 2.mp4 (26.94 MB)
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007 Interpreting the Result and Extracting the Weights and Bias.mp4 (25.96 MB)
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008 Customizing a TensorFlow 2 Model.mp4 (16.71 MB)
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001 What is a Layer.mp4 (5.17 MB)
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002 What is a Deep Net.mp4 (9.12 MB)
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003 Digging into a Deep Net.mp4 (23.7 MB)
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004 Non-Linearities and their Purpose.mp4 (22.57 MB)
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005 Activation Functions.mp4 (8.85 MB)
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006 Activation Functions Softmax Activation.mp4 (8.74 MB)
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007 Backpropagation.mp4 (20.35 MB)
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008 Backpropagation Picture.mp4 (8.06 MB)
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001 What is Overfitting.mp4 (10.81 MB)
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002 Underfitting and Overfitting for Classification.mp4 (14 MB)
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003 What is Validation.mp4 (8.38 MB)
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004 Training, Validation, and Test Datasets.mp4 (9.4 MB)
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005 N-Fold Cross Validation.mp4 (6.24 MB)
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006 Early Stopping or When to Stop Training.mp4 (10.29 MB)
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001 What is Initialization.mp4 (12.85 MB)
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002 Types of Simple Initializations.mp4 (5.73 MB)
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003 State-of-the-Art Method - (Xavier) Glorot Initialization.mp4 (5.46 MB)
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001 Stochastic Gradient Descent.mp4 (9.67 MB)
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002 Problems with Gradient Descent.mp4 (3.65 MB)
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003 Momentum.mp4 (5.18 MB)
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005 Learning Rate Schedules Visualized.mp4 (8 MB)
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007 Adam (Adaptive Moment Estimation).mp4 (7.14 MB)
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001 Preprocessing Introduction.mp4 (9.23 MB)
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002 Types of Basic Preprocessing.mp4 (3.24 MB)
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003 Standardization.mp4 (12.07 MB)
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004 Preprocessing Categorical Data.mp4 (5.44 MB)
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005 Binary and One-Hot Encoding.mp4 (23.94 MB)
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001 MNIST The Dataset.mp4 (4.53 MB)
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002 MNIST How to Tackle the MNIST.mp4 (7.95 MB)
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003 MNIST Importing the Relevant Packages and Loading the Data.mp4 (12.24 MB)
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004 MNIST Preprocess the Data - Create a Validation Set and Scale It.mp4 (22.9 MB)
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006 MNIST Preprocess the Data - Shuffle and Batch.mp4 (32.69 MB)
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008 MNIST Outline the Model.mp4 (22.08 MB)
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009 MNIST Select the Loss and the Optimizer.mp4 (10.63 MB)
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010 MNIST Learning.mp4 (30.99 MB)
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012 MNIST Testing the Model.mp4 (22.61 MB)
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001 Business Case Exploring the Dataset and Identifying Predictors.mp4 (51.28 MB)
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002 Business Case Outlining the Solution.mp4 (3.05 MB)
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003 Business Case Balancing the Dataset.mp4 (27.31 MB)
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004 Business Case Preprocessing the Data.mp4 (73.86 MB)
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006 Business Case Load the Preprocessed Data.mp4 (13.83 MB)
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008 Business Case Learning and Interpreting the Result.mp4 (27.77 MB)
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009 Business Case Setting an Early Stopping Mechanism.mp4 (43.75 MB)
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011 Business Case Testing the Model.mp4 (8.18 MB)
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001 Summary on What You've Learned.mp4 (9.86 MB)
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002 What's Further out there in terms of Machine Learning.mp4 (4.79 MB)
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004 An overview of CNNs.mp4 (13.38 MB)
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005 An Overview of RNNs.mp4 (6.97 MB)
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006 An Overview of non-NN Approaches.mp4 (16.08 MB)
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002 How to Install TensorFlow 1.mp4 (5 MB)
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004 TensorFlow Intro.mp4 (16.88 MB)
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005 Actual Introduction to TensorFlow.mp4 (9.15 MB)
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006 Types of File Formats, supporting Tensors.mp4 (8.89 MB)
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007 Basic NN Example with TF Inputs, Outputs, Targets, Weights, Biases.mp4 (17.7 MB)
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008 Basic NN Example with TF Loss Function and Gradient Descent.mp4 (15.7 MB)
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009 Basic NN Example with TF Model Output.mp4 (19.14 MB)
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001 MNIST What is the MNIST Dataset.mp4 (4.8 MB)
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002 MNIST How to Tackle the MNIST.mp4 (6.49 MB)
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003 MNIST Relevant Packages.mp4 (11.26 MB)
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004 MNIST Model Outline.mp4 (34.65 MB)
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005 MNIST Loss and Optimization Algorithm.mp4 (15.77 MB)
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006 Calculating the Accuracy of the Model.mp4 (24.45 MB)
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007 MNIST Batching and Early Stopping.mp4 (9.48 MB)
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008 MNIST Learning.mp4 (31.83 MB)
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009 MNIST Results and Testing.mp4 (45.47 MB)
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001 Business Case Getting Acquainted with the Dataset.mp4 (60.25 MB)
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002 Business Case Outlining the Solution.mp4 (4.16 MB)
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003 The Importance of Working with a Balanced Dataset.mp4 (27.25 MB)
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004 Business Case Preprocessing.mp4 (63.7 MB)
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006 Creating a Data Provider.mp4 (56.31 MB)
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007 Business Case Model Outline.mp4 (42.53 MB)
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008 Business Case Optimization.mp4 (26.93 MB)
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009 Business Case Interpretation.mp4 (18.6 MB)
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010 Business Case Testing the Model.mp4 (4.34 MB)
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011 Business Case A Comment on the Homework.mp4 (20.58 MB)
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001 What are Data, Servers, Clients, Requests, and Responses.mp4 (19.51 MB)
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002 What are Data Connectivity, APIs, and Endpoints.mp4 (60.23 MB)
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003 Taking a Closer Look at APIs.mp4 (67.06 MB)
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004 Communication between Software Products through Text Files.mp4 (21.87 MB)
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005 Software Integration - Explained.mp4 (42.94 MB)
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001 Game Plan for this Python, SQL, and Tableau Business Exercise.mp4 (19.67 MB)
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002 The Business Task.mp4 (8.35 MB)
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003 Introducing the Data Set.mp4 (24.24 MB)
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002 Importing the Absenteeism Data in Python.mp4 (19.53 MB)
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003 Checking the Content of the Data Set.mp4 (54.05 MB)
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004 Introduction to Terms with Multiple Meanings.mp4 (18 MB)
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006 Using a Statistical Approach towards the Solution to the Exercise.mp4 (13.75 MB)
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007 Dropping a Column from a DataFrame in Python.mp4 (41.25 MB)
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010 Analyzing the Reasons for Absence.mp4 (27.61 MB)
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011 Obtaining Dummies from a Single Feature.mp4 (69.76 MB)
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015 More on Dummy Variables A Statistical Perspective.mp4 (5.82 MB)
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016 Classifying the Various Reasons for Absence.mp4 (59.2 MB)
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017 Using concat() in Python.mp4 (27.33 MB)
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020 Reordering Columns in a Pandas DataFrame in Python.mp4 (9.99 MB)
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023 Creating Checkpoints while Coding in Jupyter.mp4 (17.33 MB)
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026 Analyzing the Dates from the Initial Data Set.mp4 (40.13 MB)
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027 Extracting the Month Value from the Date Column.mp4 (33.93 MB)
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028 Extracting the Day of the Week from the Date Column.mp4 (19.11 MB)
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030 Analyzing Several Straightforward Columns for this Exercise.mp4 (20.09 MB)
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031 Working on Education, Children, and Pets.mp4 (16.92 MB)
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032 Final Remarks of this Section.mp4 (19.74 MB)
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004 Standardizing the Data.mp4 (15.15 MB)
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005 Splitting the Data for Training and Testing.mp4 (41.89 MB)
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006 Fitting the Model and Assessing its Accuracy.mp4 (35.29 MB)
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008 Interpreting the Coefficients for Our Problem.mp4 (24.77 MB)
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012 Testing the Model We Created.mp4 (31.6 MB)
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002 Deploying the 'absenteeism module' - Part I.mp4 (19.64 MB)
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003 Deploying the 'absenteeism module' - Part II.mp4 (45.15 MB)
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002 Analyzing Age vs Probability in Tableau.mp4 (38.66 MB)
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004 Analyzing Reasons vs Probability in Tableau.mp4 (40.24 MB)
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006 Analyzing Transportation Expense vs Probability in Tableau.mp4 (19.78 MB)
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001 Using the format() Method.mp4 (25.69 MB)
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002 Iterating Over Range Objects.mp4 (12.62 MB)
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003 Introduction to Nested For Loops.mp4 (12.13 MB)
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004 Triple Nested For Loops.mp4 (33 MB)
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005 List Comprehensions.mp4 (43.2 MB)
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006 Anonymous (Lambda) Functions.mp4 (30.34 MB)
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001 Introduction to pandas Series.mp4 (22.21 MB)
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002 Working with Methods in Python - Part I.mp4 (19.55 MB)
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003 Working with Methods in Python - Part II.mp4 (9 MB)
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004 Parameters and Arguments in pandas.mp4 (21.14 MB)
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005 Using unique() and nunique().mp4 (24.29 MB)
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006 Using sort values().mp4 (21.04 MB)
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007 Introduction to pandas DataFrames - Part I.mp4 (10.61 MB)
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008 Introduction to pandas DataFrames - Part II.mp4 (17.83 MB)
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009 pandas DataFrames - Common Attributes.mp4 (29.79 MB)
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010 Data Selection in pandas DataFrames.mp4 (37.26 MB)
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011 pandas DataFrames - Indexing with iloc[].mp4 (32.22 MB)
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012 pandas DataFrames - Indexing with loc[].mp4 (20.69 MB)
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001 An Introduction to Working with Files in Python.mp4 (12.03 MB)
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002 File vs File Object, Reading vs Parsing Data.mp4 (9.42 MB)
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003 Structured, Semi-Structured and Unstructured Data.mp4 (11.07 MB)
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004 Text Files and Data Connectivity.mp4 (10.81 MB)
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005 Importing Data in Python - Principles.mp4 (16.72 MB)
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006 Plain Text Files, Flat Files and More.mp4 (13.16 MB)
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007 Text Files of Fixed Width.mp4 (4.83 MB)
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008 Common Naming Conventions.mp4 (8.21 MB)
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009 Importing Text Files - open().mp4 (28.19 MB)
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010 Importing Text Files - with open().mp4 (26.26 MB)
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011 Importing csv Files - Part I.mp4 (49.87 MB)
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012 Importing csv Files - Part II.mp4 (10.92 MB)
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013 Importing csv Files - Part III.mp4 (75.01 MB)
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014 Importing Data with index col.mp4 (11.63 MB)
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015 Importing Data with loadtxt() and genfromtxt().mp4 (56.33 MB)
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016 Importing Data - Partial Cleaning While Importing Data.mp4 (43.91 MB)
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018 Importing Data from json Files.mp4 (81.95 MB)
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019 An Introduction to Working with Excel Files in Python.mp4 (42.98 MB)
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020 Working with Excel ( xlsx) Data.mp4 (14.41 MB)
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021 Importing Data in Python - an Important Exercise.mp4 (43.01 MB)
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022 Importing Data with the squeeze() Method.mp4 (22.42 MB)
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023 Importing Files in Jupyter.mp4 (19.57 MB)
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024 Saving Your Data with pandas.mp4 (21.06 MB)
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025 Saving Your Data with NumPy - Part I - npy.mp4 (18.91 MB)
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026 Saving Your Data with NumPy - Part II - npz.mp4 (23.26 MB)
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027 Saving Your Data with NumPy - Part III - csv.mp4 (20.83 MB)
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029 Working with Text Files in Python - Conclusion.mp4 (2.11 MB)
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