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13. Introduction to Matplotlib.mp4

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Python Machine Learning -all concepts a-z

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1 - Introduction to Machine Learning

10 - Feature Engineering

11 - Saving & Loading Models

12 - Practical ML Projects

13 - Deployment Basics

14 - Best Practices & ML Workflow

15 - Interview Preparation

2 - Python for Machine Learning

3 - ML Libraries in Python

14. Matplotlib & Seaborn basics.mp4

MP4

3.4 MB

1 matching file, 66 total files.

Seeders: 25
Leechers: 14
Size: 992.3 MB
Files: 66
Age: 3 months ago

992.3 MB

3 months ago

Udemy - Python Programming Zero to Hero - Learn Python Step by Step

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1 - Introduction to Python & Setup

10 - Python Modules and Packages

11 - Intermediate to Advanced Python

12 - Working with APIs and Web Requests

13 - Automation and Scripting

14 - Introduction to Data Science with Python

42. Installing Pandas, Numpy, Matplotlib.mp4

MP4

51.1 MB

1 matching file, 45 total files.

Seeders: 19
Leechers: 0
Size: 2 GB
Files: 45
Age: 5 months ago

2 GB

5 months ago

Udemy - Complete Machine Learning and Data Science With Python ML A-Z

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1 - Introduction

10 - Project Customer Segmentation using Clustering

11 - Project Fake News Detection using machine learning Python

12 - Project COVID19 Coronavirus Infection Probability using machine learning

13 - Miscellaneous

14 - Python Crash Course

2 - Installation and Colab

3 - Python for Data Analysis Numpy

4 - Python for Data Analysis Pandas

5 - Python for Data Visualization Matplotlib

6 - Supervised Machine Learning

29 - how to implement Logistic Regression.mp4

MP4

26.3 MB

34 - Introduction to Naive Bayes Classifier for Text Classification.mp4

MP4

12.1 MB

36 - Introduction to Decision Tree.mp4

MP4

33.4 MB

7 - UnSupervised Machine Learning

8 - Reinforcement Learning

51 - Introduction to Reinforcement Learning.mp4

MP4

38.7 MB

4 matching files, 187 total files.

Seeders: 16
Leechers: 8
Size: 3.1 GB
Files: 187
Age: 6 months ago

187

3.1 GB

6 months ago

Udemy - Machine Learning Using Python Programming

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1 - Introduction to Machine Learning

10 - Support Vector Machines

11 - K Nearest Neighbors for Classification and Regression

12 - Decision Tree Classifier Algorithm

13 - Random Forest Classifier Algorithm

14 - Naive Bayes Algorithm

15 - Resources

Notebooks

16 - KMeans Clustering

2 - Types of Machine Learning

3 - The Machine Learning Pipeline

4 - Numpy Library

5 - Pandas Library

6 - Analysis of Datasets using Pandas and Matplotlib Library

27 - 26 Loading the dataset Important.mp4

MP4

32.3 MB

28 - 27 Analysis of Datasets I.mp4

MP4

42 MB

29 - 28 Analysis of Datasets by Plotting II.mp4

MP4

71.1 MB

7 - The Scikitlearn Library and Preprocessing Techniques

30 - 29 Working with Iris Dataset from sklearn.mp4

MP4

194.1 MB

31 - 30 Binarization.mp4

MP4

43.2 MB

32 - 31 Feature Scaling.mp4

MP4

46.9 MB

8 - Supervised Learning Linear Regression

33 - 32 Analysis of Linear Regression.mp4

MP4

73.8 MB

34 - Use of Gradient Descent Optimizer.mp4

MP4

33 MB

35 - The Gradient Descent Optimizer Algorithm.mp4

MP4

81.1 MB

36 - 33 Demand vs Price Problem to understand Linear Regression.mp4

MP4

71.3 MB

37 - 34 Implementation of Linear Regression I.mp4

MP4

75.8 MB

38 - 35 Implementation of Linear Regression II.mp4

MP4

48.2 MB

39 - 36 Visualizing the LBF using matplotlib.mp4

MP4

23.3 MB

9 - Logistic Regression for Classification Problems

40 - 37 Why does Linear Regression fail for a classification problem.mp4	MP4	39.1 MB
41 - 38 The Sigmoid function in Logistic Regression.mp4	MP4	24 MB
42 - 39 The Confusion Matrix.mp4	MP4	60.1 MB
43 - 40 Implementation of Logistic Regression I.mp4	MP4	150.3 MB
44 - 41 Creating an heatmap of the confusion matrix.mp4	MP4	22.1 MB