Udemy - Complete Data Science & Machine Learning A-Z with Python

Files Included :

1 Installing Anaconda Distribution for Windows.mp4 (118.32 MB)
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3 Installing Anaconda Distribution for MacOs.mp4 (46.31 MB)
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5 Installing Anaconda Distribution for Linux.mp4 (114.75 MB)
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1 Element Selection Operations in Pandas DataFrames Lesson 1.mp4 (29.9 MB)
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2 Element Selection Operations in Pandas DataFrames Lesson 2.mp4 (31.84 MB)
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3 Top Level Element Selection in Pandas DataFramesLesson 1.mp4 (38.29 MB)
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4 Top Level Element Selection in Pandas DataFramesLesson 2.mp4 (31.41 MB)
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5 Top Level Element Selection in Pandas DataFramesLesson 3.mp4 (22.11 MB)
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6 Element Selection with Conditional Operations in.mp4 (46.37 MB)
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1 Adding Columns to Pandas Data Frames.mp4 (33.58 MB)
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2 Removing Rows and Columns from Pandas Data frames.mp4 (15.56 MB)
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3 Null Values in Pandas Dataframes.mp4 (66.96 MB)
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4 Dropping Null Values Dropna() Function.mp4 (34.54 MB)
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5 Filling Null Values Fillna() Function.mp4 (51.62 MB)
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6 Setting Index in Pandas DataFrames.mp4 (39.7 MB)
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1 Multi-Index and Index Hierarchy in Pandas DataFrames.mp4 (42.66 MB)
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2 Element Selection in Multi-Indexed DataFrames.mp4 (24.58 MB)
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3 Selecting Elements Using the xs() Function in Multi-Indexed DataFrames.mp4 (31.25 MB)
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1 Concatenating Pandas Dataframes Concat Function.mp4 (63.84 MB)
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2 Merge Pandas Dataframes Merge() Function Lesson 1.mp4 (57.29 MB)
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3 Merge Pandas Dataframes Merge() Function Lesson 2.mp4 (30.55 MB)
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4 Merge Pandas Dataframes Merge() Function Lesson 3.mp4 (60.17 MB)
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5 Merge Pandas Dataframes Merge() Function Lesson 4.mp4 (40.68 MB)
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6 Joining Pandas Dataframes Join() Function.mp4 (56.05 MB)
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1 Loading a Dataset from the Seaborn Library.mp4 (37.72 MB)
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2 Examining the Data Set 1.mp4 (42.9 MB)
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3 Aggregation Functions in Pandas DataFrames.mp4 (90.69 MB)
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4 Examining the Data Set 2.mp4 (46.58 MB)
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5 Coordinated Use of Grouping and Aggregation Functions in Pandas Dataframes.mp4 (88.12 MB)
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6 Advanced Aggregation Functions Aggregate() Function.mp4 (29.22 MB)
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7 Advanced Aggregation Functions Filter() Function.mp4 (24.45 MB)
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8 Advanced Aggregation Functions Transform() Function.mp4 (47.09 MB)
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9 Advanced Aggregation Functions Apply() Function.mp4 (41.42 MB)
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1 Examining the Data Set 3.mp4 (39.11 MB)
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2 Pivot Tables in Pandas Library.mp4 (54.23 MB)
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1 Accessing and Making Files Available.mp4 (34.61 MB)
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2 Data Entry with Csv and Txt Files.mp4 (64.34 MB)
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3 Data Entry with Excel Files.mp4 (21.84 MB)
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4 Outputting as an CSV Extension.mp4 (35.7 MB)
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5 Outputting as an Excel File.mp4 (19.74 MB)
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1 Introduction to Data Visualization with Python.mp4 (12.85 MB)
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1 Data Types in Python.mp4 (47.07 MB)
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10 Exercise - Solution in Python.mp4 (51.89 MB)
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2 Operators in Python.mp4 (35.71 MB)
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3 Conditionals in Python.mp4 (41.23 MB)
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4 Loops in Python.mp4 (58.81 MB)
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5 Lists, Tuples, Dictionaries and Sets in pyhton.mp4 (75.33 MB)
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6 Data Type Operators and Methods in Python.mp4 (43.86 MB)
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7 Modules in Python.mp4 (23.95 MB)
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8 Functions in Python.mp4 (28.93 MB)
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9 Exercise - Analyse in Python.mp4 (8.46 MB)
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1 Introduction to NumPy Library.mp4 (45.27 MB)
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2 The Power of NumPy.mp4 (59.87 MB)
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1 Logic of Object Oriented Programming.mp4 (17.38 MB)
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2 Constructor in Object Oriented Programming (OOP).mp4 (35.84 MB)
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3 Methods in Object Oriented Programming (OOP).mp4 (25.1 MB)
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4 Inheritance in Object Oriented Programming (OOP).mp4 (34.58 MB)
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5 Overriding and Overloading in Object Oriented Programming (OOP).mp4 (62.7 MB)
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1 What is Matplotlib.mp4 (19.06 MB)
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2 Using Pyplot.mp4 (28.22 MB)
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3 Pyplot – Pylab - Matplotlib.mp4 (28.37 MB)
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4 Figure, Subplot and Axex.mp4 (69.89 MB)
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5 Figure Customization.mp4 (63.29 MB)
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6 Plot Customization.mp4 (27.38 MB)
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7 Grid, Spines, Ticks.mp4 (23.89 MB)
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8 Basic Plots in Matplotlib I.mp4 (111.17 MB)
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9 Basic Plots in Matplotlib II.mp4 (54.82 MB)
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1 What is Seaborn.mp4 (13.59 MB)
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2 Controlling Figure Aesthetics in Seaborn.mp4 (41.82 MB)
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3 Example in Seaborn.mp4 (54.9 MB)
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4 Color Palettes in Seaborn.mp4 (48.32 MB)
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5 Basic Plots in Seaborn.mp4 (98.84 MB)
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6 Multi-Plots in Seaborn.mp4 (42.98 MB)
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7 Regression Plots and Squarify in Seaborn.mp4 (60.1 MB)
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1 What is Geoplotlib.mp4 (34.18 MB)
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2 Example - 1.mp4 (38.85 MB)
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3 Example - 2.mp4 (81.14 MB)
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4 Example - 3.mp4 (51.28 MB)
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1 What is Machine Learning.mp4 (27.58 MB)
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2 Machine Learning Terminology.mp4 (14.03 MB)
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1 Classification vs Regression in Machine Learning.mp4 (19.89 MB)
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2 Machine Learning Model Performance Evaluation Classification Error Metrics.mp4 (100.26 MB)
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3 Evaluating Performance Regression Error Metrics in Python.mp4 (45.7 MB)
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4 Machine Learning With Python.mp4 (92.24 MB)
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1 What is Supervised Learning in Machine Learning.mp4 (31.69 MB)
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1 Linear Regression Algorithm Theory in Machine Learning A-Z.mp4 (34.06 MB)
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2 Linear Regression Algorithm With Python Part 1.mp4 (76.17 MB)
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3 Linear Regression Algorithm With Python Part 2.mp4 (106.94 MB)
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4 Linear Regression Algorithm With Python Part 3.mp4 (70.28 MB)
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5 Linear Regression Algorithm With Python Part 4.mp4 (90 MB)
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1 What is Bias Variance Trade-Off.mp4 (55.03 MB)
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1 What is Logistic Regression Algorithm in Machine Learning.mp4 (27.84 MB)
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2 Logistic Regression Algorithm with Python Part 1.mp4 (72.22 MB)
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3 Logistic Regression Algorithm with Python Part 2.mp4 (81.46 MB)
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4 Logistic Regression Algorithm with Python Part 3.mp4 (47.35 MB)
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5 Logistic Regression Algorithm with Python Part 4.mp4 (47.17 MB)
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6 Logistic Regression Algorithm with Python Part 5.mp4 (39.35 MB)
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1 Creating NumPy Array with The Array() Function.mp4 (29.5 MB)
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2 Creating NumPy Array with Zeros() Function.mp4 (24.06 MB)
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3 Creating NumPy Array with Ones() Function.mp4 (15.88 MB)
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4 Creating NumPy Array with Full() Function.mp4 (11.18 MB)
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5 Creating NumPy Array with Arange() Function.mp4 (12.1 MB)
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6 Creating NumPy Array with Eye() Function.mp4 (12.55 MB)
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7 Creating NumPy Array with Linspace() Function.mp4 (7.34 MB)
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8 Creating NumPy Array with Random() Function.mp4 (43.3 MB)
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9 Properties of NumPy Array.mp4 (21.98 MB)
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1 K-Fold Cross-Validation Theory.mp4 (17.45 MB)
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2 K-Fold Cross-Validation with Python.mp4 (34.67 MB)
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1 K Nearest Neighbors Algorithm Theory.mp4 (28.66 MB)
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2 K Nearest Neighbors Algorithm with Python Part 1.mp4 (35.03 MB)
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3 K Nearest Neighbors Algorithm with Python Part 2.mp4 (59.37 MB)
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4 K Nearest Neighbors Algorithm with Python Part 3.mp4 (31.4 MB)
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1 Hyperparameter Optimization Theory.mp4 (33.14 MB)
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2 Hyperparameter Optimization with Python.mp4 (47.47 MB)
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1 Decision Tree Algorithm Theory.mp4 (35.75 MB)
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2 Decision Tree Algorithm with Python Part 1.mp4 (31.53 MB)
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3 Decision Tree Algorithm with Python Part 2.mp4 (48.92 MB)
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4 Decision Tree Algorithm with Python Part 3.mp4 (14.72 MB)
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5 Decision Tree Algorithm with Python Part 4.mp4 (42.49 MB)
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6 Decision Tree Algorithm with Python Part 5.mp4 (32.67 MB)
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1 Random Forest Algorithm Theory.mp4 (22.89 MB)
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2 Random Forest Algorithm with Pyhon Part 1.mp4 (38.61 MB)
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3 Random Forest Algorithm with Pyhon Part 2.mp4 (38.72 MB)
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1 Support Vector Machine Algorithm Theory.mp4 (21.84 MB)
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2 Support Vector Machine Algorithm with Python Part 1.mp4 (35.59 MB)
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3 Support Vector Machine Algorithm with Python Part 2.mp4 (41.72 MB)
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4 Support Vector Machine Algorithm with Python Part 3.mp4 (34.77 MB)
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5 Support Vector Machine Algorithm with Python Part 4.mp4 (37.55 MB)
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1 Unsupervised Learning Overview.mp4 (16.91 MB)
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1 K Means Clustering Algorithm Theory.mp4 (17.13 MB)
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2 K Means Clustering Algorithm with Python Part 1.mp4 (29.96 MB)
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3 K Means Clustering Algorithm with Python Part 2.mp4 (29.64 MB)
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4 K Means Clustering Algorithm with Python Part 3.mp4 (27.75 MB)
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5 K Means Clustering Algorithm with Python Part 4.mp4 (29.03 MB)
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1 Hierarchical Clustering Algorithm Theory.mp4 (28.55 MB)
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2 Hierarchical Clustering Algorithm with Python Part 2.mp4 (35.52 MB)
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3 Hierarchical Clustering Algorithm with Python Part 2.mp4 (28.89 MB)
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1 Principal Component Analysis (PCA) Theory.mp4 (37.96 MB)
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2 Principal Component Analysis (PCA) with Python Part 1.mp4 (26.02 MB)
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3 Principal Component Analysis (PCA) with Python Part 2.mp4 (8.42 MB)
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4 Principal Component Analysis (PCA) with Python Part 3.mp4 (37.25 MB)
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1 Reshaping a NumPy Array Reshape() Function.mp4 (26.16 MB)
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2 Identifying the Largest Element of a Numpy Array.mp4 (15.12 MB)
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3 Detecting Least Element of Numpy Array Min(), Ar.mp4 (10.17 MB)
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4 Concatenating Numpy Arrays Concatenate() Functio.mp4 (38.36 MB)
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5 Splitting One-Dimensional Numpy Arrays The Split.mp4 (20.9 MB)
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6 Splitting Two-Dimensional Numpy Arrays Split(),.mp4 (35.73 MB)
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7 Sorting Numpy Arrays Sort() Function.mp4 (17.02 MB)
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1 What is the Recommender System Part 1.mp4 (23.04 MB)
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2 What is the Recommender System Part 2.mp4 (17.96 MB)
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1 What is Kaggle.mp4 (129.67 MB)
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3 Registering on Kaggle and Member Login Procedures.mp4 (43.48 MB)
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5 Getting to Know the Kaggle Homepage.mp4 (122.93 MB)
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1 Competitions on Kaggle Lesson 1.mp4 (188.17 MB)
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2 Competitions on Kaggle Lesson 2.mp4 (191.68 MB)
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1 Datasets on Kaggle.mp4 (133.23 MB)
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1 Examining the Code Section in Kaggle Lesson 1.mp4 (79.53 MB)
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2 Examining the Code Section in Kaggle Lesson 2.mp4 (105.81 MB)
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3 Examining the Code Section in Kaggle Lesson 3.mp4 (159.89 MB)
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1 What is Discussion on Kaggle.mp4 (40.63 MB)
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1 Courses in Kaggle.mp4 (52.14 MB)
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2 Ranking Among Users on Kaggle.mp4 (107.04 MB)
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3 Blog and Documentation Sections.mp4 (40.85 MB)
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1 User Page Review on Kaggle.mp4 (81.5 MB)
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2 Treasure in The Kaggle.mp4 (74.64 MB)
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3 Publishing Notebooks on Kaggle.mp4 (38.2 MB)
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4 What Should Be Done to Achieve Success in Kaggle.mp4 (58.48 MB)
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1 First Step to the Hearth Attack Prediction Project.mp4 (117.14 MB)
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3 Notebook Design to be Used in the Project.mp4 (104.93 MB)
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5 Examining the Project Topic.mp4 (76.51 MB)
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6 Recognizing Variables In Dataset.mp4 (126.87 MB)
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1 Required Python Libraries.mp4 (63.55 MB)
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2 Loading the Statistics Dataset in Data Science.mp4 (10 MB)
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3 Initial analysis on the dataset.mp4 (63.96 MB)
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1 Indexing Numpy Arrays,.mp4 (26.56 MB)
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2 Slicing One-Dimensional Numpy Arrays.mp4 (22.27 MB)
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3 Slicing Two-Dimensional Numpy Arrays.mp4 (34.27 MB)
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4 Assigning Value to One-Dimensional Arrays.mp4 (18.2 MB)
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5 Assigning Value to Two-Dimensional Array.mp4 (35.4 MB)
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6 Fancy Indexing of One-Dimensional Arrrays.mp4 (20.49 MB)
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7 Fancy Indexing of Two-Dimensional Arrrays.mp4 (45.75 MB)
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8 Combining Fancy Index with Normal Indexing.mp4 (12.65 MB)
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9 Combining Fancy Index with Normal Slicing.mp4 (16.46 MB)
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1 Examining Missing Values.mp4 (45.79 MB)
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2 Examining Unique Values.mp4 (44.54 MB)
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3 Separating variables (Numeric or Categorical).mp4 (15.81 MB)
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4 Examining Statistics of Variables.mp4 (91.37 MB)
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1 Numeric Variables (Analysis with Distplot) Lesson 1.mp4 (80.35 MB)
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2 Numeric Variables (Analysis with Distplot) Lesson 2.mp4 (19.75 MB)
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3 Categoric Variables (Analysis with Pie Chart) Lesson 1.mp4 (74.74 MB)
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4 Categoric Variables (Analysis with Pie Chart) Lesson 2.mp4 (84.06 MB)
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5 Examining the Missing Data According to the Analysis Result.mp4 (53.78 MB)
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1 Numeric Variables – Target Variable (Analysis with FacetGrid) Lesson 1.mp4 (49.37 MB)
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10 Numerical - Categorical Variables (Analysis with Swarm Plot) Lesson 2.mp4 (68.08 MB)
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11 Numerical - Categorical Variables (Analysis with Box Plot) Lesson 1.mp4 (38.07 MB)
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12 Numerical - Categorical Variables (Analysis with Box Plot) Lesson 2.mp4 (35.47 MB)
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13 Relationships between variables (Analysis with Heatmap) Lesson 1.mp4 (36.36 MB)
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14 Relationships between variables (Analysis with Heatmap) Lesson 2.mp4 (90.67 MB)
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2 Numeric Variables – Target Variable (Analysis with FacetGrid) Lesson 2.mp4 (35.64 MB)
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3 Categoric Variables – Target Variable (Analysis with Count Plot) Lesson 1.mp4 (24.15 MB)
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4 Categoric Variables – Target Variable (Analysis with Count Plot) Lesson 2.mp4 (56.27 MB)
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5 Examining Numeric Variables Among Themselves (Analysis with Pair Plot) Lesson 1.mp4 (28.31 MB)
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6 Examining Numeric Variables Among Themselves (Analysis with Pair Plot) Lesson 2.mp4 (47.14 MB)
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7 Feature Scaling with the Robust Scaler Method.mp4 (35.2 MB)
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8 Creating a New DataFrame with the Melt() Function.mp4 (52.89 MB)
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9 Numerical - Categorical Variables (Analysis with Swarm Plot) Lesson 1.mp4 (41.72 MB)
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1 Dropping Columns with Low Correlation.mp4 (26.83 MB)
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10 Feature Scaling with the Robust Scaler Method for Machine Learning Algorithms.mp4 (11.45 MB)
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11 Separating Data into Test and Training Set.mp4 (29.75 MB)
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2 Visualizing Outliers.mp4 (34.89 MB)
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3 Dealing with Outliers – Trtbps Variable Lesson 1.mp4 (42.82 MB)
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4 Dealing with Outliers – Trtbps Variable Lesson 2.mp4 (43.91 MB)
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5 Dealing with Outliers – Thalach Variable.mp4 (36.24 MB)
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6 Dealing with Outliers – Oldpeak Variable.mp4 (36.06 MB)
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7 Determining Distributions of Numeric Variables.mp4 (25.17 MB)
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8 Transformation Operations on Unsymmetrical Data.mp4 (24.01 MB)
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9 Applying One Hot Encoding Method to Categorical Variables.mp4 (24.09 MB)
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1 Logistic Regression.mp4 (29.34 MB)
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2 Cross Validation.mp4 (30.21 MB)
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3 Roc Curve and Area Under Curve (AUC).mp4 (41.71 MB)
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4 Hyperparameter Optimization (with GridSearchCV).mp4 (58.77 MB)
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5 Decision Tree Algorithm.mp4 (25.7 MB)
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6 Support Vector Machine Algorithm.mp4 (24.52 MB)
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7 Random Forest Algorithm.mp4 (29.78 MB)
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8 Hyperparameter Optimization (with GridSearchCV).mp4 (52.65 MB)
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1 Project Conclusion and Sharing.mp4 (28.66 MB)
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1 Operations with Comparison Operators.mp4 (21.14 MB)
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2 Arithmetic Operations in Numpy.mp4 (71.82 MB)
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3 Statistical Operations in Numpy.mp4 (32.02 MB)
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4 Solving Second-Degree Equations with NumPy.mp4 (24.2 MB)
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1 Introduction to Pandas Library.mp4 (33.93 MB)
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1 Creating a Pandas Series with a List.mp4 (39.19 MB)
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2 Creating a Pandas Series with a Dictionary.mp4 (18.29 MB)
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3 Creating Pandas Series with NumPy Array.mp4 (11.97 MB)
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4 Object Types in Series.mp4 (19.58 MB)
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5 Examining the Primary Features of the Pandas Seri.mp4 (18.94 MB)
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6 Most Applied Methods on Pandas Series.mp4 (48.21 MB)
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7 Indexing and Slicing Pandas Series.mp4 (29.89 MB)
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1 Creating Pandas DataFrame with List.mp4 (22.57 MB)
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2 Creating Pandas DataFrame with NumPy Array.mp4 (12.1 MB)
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3 Creating Pandas DataFrame with Dictionary.mp4 (15.84 MB)
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4 Examining the Properties of Pandas DataFrames.mp4 (25.94 MB)
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