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4. Matplotlib Introduction.vtt

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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

15 - Matplotlib Introduction English.vtt

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12.1 KB

16 - Matplotlib Bar Graphs English.vtt

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5.1 KB

17 - Matplotlib Histogram English.vtt

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18 - Matplotlib Scatter Plot English.vtt

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19 - Matplotlib Area Plot English.vtt

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20 - Matplotlib Pie Chart English.vtt

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21 - Matplotlib Subplots English.vtt

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6 - Supervised Machine Learning

22 - What is Supervised Machine Learning and Linear Regression Algorithm English.vtt	VTT	7.7 KB
23 - Implementation of Linear Regression English.vtt	VTT	8.8 KB
24 - Plot Linear Regression English.vtt	VTT	6.6 KB
25 - Implementation of Multi Linear Regression English.vtt	VTT	5.5 KB
26 - Example 2 Multilinear Regression English.vtt	VTT	7.1 KB
27 - Use Case Boston Housing Price Prediction English.vtt	VTT	13 KB
28 - Save Model English.vtt	VTT	7.4 KB
29 - how to implement Logistic Regression English.vtt	VTT	5.1 KB
30 - Logistic Regression on Iris Flower Dataset English.vtt	VTT	10.1 KB
31 - Logistic Regression on Digits Dataset English.vtt	VTT	6.4 KB
32 - Naive Bayes Classifier English.vtt	VTT	6.5 KB
33 - Implementation of Naive Bayes classifier on Wine Dataset English.vtt	VTT	8.5 KB
34 - Introduction to Naive Bayes Classifier for Text Classification English.vtt	VTT	3.5 KB

20 matching files shown out of 43 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 English.vtt

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6.7 KB

28 - 27 Analysis of Datasets I English.vtt

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29 - 28 Analysis of Datasets by Plotting II English.vtt

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7 - The Scikitlearn Library and Preprocessing Techniques

30 - 29 Working with Iris Dataset from sklearn English.vtt

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31 - 30 Binarization English.vtt

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32 - 31 Feature Scaling English.vtt

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8 - Supervised Learning Linear Regression

33 - 32 Analysis of Linear Regression English.vtt

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34 - Use of Gradient Descent Optimizer English.vtt

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35 - The Gradient Descent Optimizer Algorithm English.vtt

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

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37 - 34 Implementation of Linear Regression I English.vtt

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38 - 35 Implementation of Linear Regression II English.vtt

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39 - 36 Visualizing the LBF using matplotlib English.vtt

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9 - Logistic Regression for Classification Problems

40 - 37 Why does Linear Regression fail for a classification problem English.vtt	VTT	11.2 KB
41 - 38 The Sigmoid function in Logistic Regression English.vtt	VTT	6.3 KB
42 - 39 The Confusion Matrix English.vtt	VTT	14.2 KB
43 - 40 Implementation of Logistic Regression I English.vtt	VTT	20.2 KB
44 - 41 Creating an heatmap of the confusion matrix English.vtt	VTT	4.1 KB