UDEMY Machine Learning and Data Science A-Z Hands-on Python (2022) BOOKWARE-iLEARN

Download Now


Files Included :

1 Course Content.mp4 (17.07 MB)
MP4
10 NumPy2.mp4 (56.91 MB)
MP4
11 NumPy3.mp4 (84.52 MB)
MP4
12 NumPy4.mp4 (56.56 MB)
MP4
13 NumPy5.mp4 (152.64 MB)
MP4
14 NumPy6.mp4 (134.5 MB)
MP4
15 Pandas1.mp4 (95.61 MB)
MP4
16 Pandas2.mp4 (116.94 MB)
MP4
17 Pandas3.mp4 (117.83 MB)
MP4
18 Pandas4.mp4 (203.04 MB)
MP4
19 Visualization with Matplotlib1.mp4 (99.45 MB)
MP4
2 What is Machine Learning Some Basic Terms.mp4 (25.82 MB)
MP4
20 Visualization with Matplotlib2.mp4 (205.24 MB)
MP4
21 Visualization with Matplotlib3.mp4 (188.84 MB)
MP4
22 Visualization with Matplotlib4.mp4 (142.99 MB)
MP4
23 Visualization with Matplotlib5.mp4 (129.25 MB)
MP4
24 Reading and Modifying a Dataset.mp4 (154.55 MB)
MP4
25 Statistics1.mp4 (34.04 MB)
MP4
26 Statistics2.mp4 (207.49 MB)
MP4
27 Statistics3 - Covariance.mp4 (107.48 MB)
MP4
28 Missing Values1.mp4 (129.64 MB)
MP4
29 Missing Values2.mp4 (219.38 MB)
MP4
30 Outlier Detection1.mp4 (73.2 MB)
MP4
31 Outlier Detection2.mp4 (130.66 MB)
MP4
32 Outlier Detection3.mp4 (31.01 MB)
MP4
33 Concatenation.mp4 (65.88 MB)
MP4
34 Dummy Variable.mp4 (57.59 MB)
MP4
35 Normalization.mp4 (186.87 MB)
MP4
36 Learning Types.mp4 (45.44 MB)
MP4
37 Supervised Learning Models - Introduction and Understanding the Data.mp4 (233.75 MB)
MP4
38 k-NN Concepts.mp4 (48.03 MB)
MP4
39 k-NN Model Development.mp4 (140.65 MB)
MP4
4 Python IDE.mp4 (7.51 MB)
MP4
40 k-NN Training-Set and Test-Set Creation.mp4 (228.42 MB)
MP4
41 Decision Tree Concepts.mp4 (25.62 MB)
MP4
42 Decision Tree Model Development.mp4 (66.84 MB)
MP4
43 Decision Tree - Cross Validation.mp4 (54.64 MB)
MP4
44 Naive Bayes Concepts.mp4 (59.23 MB)
MP4
45 Naive Bayes Model Development.mp4 (58.95 MB)
MP4
46 Logistic Regression Concepts.mp4 (10.85 MB)
MP4
47 Logistic Regression Model Development.mp4 (112.12 MB)
MP4
48 Model Evaluation Concepts.mp4 (83.47 MB)
MP4
49 Model Evaluation - Calculating with Python.mp4 (174.04 MB)
MP4
5 IDE Installation.mp4 (22.28 MB)
MP4
50 Simple and Multiple Linear Regression Concepts.mp4 (212.19 MB)
MP4
51 Multiple Linear Regression - Model Development.mp4 (75.59 MB)
MP4
52 Evaluation Metrics - Concepts.mp4 (49.47 MB)
MP4
53 Evaluation Metrics - Implementation.mp4 (159.9 MB)
MP4
54 Polynomial Linear Regression Concepts.mp4 (26.39 MB)
MP4
55 Polynomial Linear Regression Model Development.mp4 (219.12 MB)
MP4
56 Random Forest Concepts.mp4 (30.23 MB)
MP4
57 Random Forest Model Development.mp4 (246.24 MB)
MP4
58 Support Vector Regression Concepts.mp4 (26.97 MB)
MP4
59 Support Vector Regression Model Development.mp4 (121.01 MB)
MP4
6 Installation of Required Libraries.mp4 (70.78 MB)
MP4
60 Introduction.mp4 (38.11 MB)
MP4
61 K-means Concepts1.mp4 (44.53 MB)
MP4
62 K-means Concepts2.mp4 (21.28 MB)
MP4
63 K-means Model Development1.mp4 (35.98 MB)
MP4
64 K-means Model Development2.mp4 (103.83 MB)
MP4
65 K-means - Model Evaluation.mp4 (102.4 MB)
MP4
66 DBSCAN Concepts.mp4 (26.85 MB)
MP4
67 DBSCAN Model Development.mp4 (86.87 MB)
MP4
68 Hierarchical Clustering Concepts.mp4 (24.29 MB)
MP4
69 Hierarchical Clustering Model Development.mp4 (145.89 MB)
MP4
7 Spyder Interface.mp4 (46.36 MB)
MP4
70 Introduction.mp4 (17.02 MB)
MP4
71 Support Vector Regression - Model Tuning.mp4 (125.61 MB)
MP4
72 K-Means - Model Tuning.mp4 (15.3 MB)
MP4
73 k-NN - Model Tuning.mp4 (133.64 MB)
MP4
74 Overfitting and Underfitting.mp4 (72.09 MB)
MP4
9 NumPy1.mp4 (37.49 MB)
MP4