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Machine Learning Git Codebook

Lesson 1 : Introduction to Numpy (Video)
Lesson 2 : Introduction to Pandas
Lesson 3 : Plotting in Python
Lesson 4 : Regression Models
Lesson 5 : Preprocessing Data
Lesson 6 : Decision Trees
Lesson 7 : Naive Bayes
Lesson 8 : Feature Unions
Lesson 9 : Model Selection and Evaluation
Lesson 10 : Feature Selection Techniques Lesson 11 : Nearest Neighbors

Case Study of Classic ML Problems

Case 1 : Linear Regression
Case 2 : Cancer Prediction
Case 3 : Online Learning
Case 4 : Customer Churn Prediction
Case 5 : Income Prediction
Case 6 : Predicting Employee Exit
Case 7 : Face Generation

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Python - https://www.edyoda.com/resources/videolisting/98/
Angular - https://www.edyoda.com/resources/videolisting/1227/
Machine Learning - https://www.edyoda.com/resources/videolisting/1416/
Dog Breed Prediction Project - https://www.edyoda.com/resources/videolisting/1336/
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Numpy - https://www.edyoda.com/resources/videolisting/1263/
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Deep Reinforcement Learning - https://www.edyoda.com/resources/videolisting/1421/
Knowledge Graphs, Deep Learning, Reasoning - https://www.edyoda.com/resources/videolisting/1420/
Natural Language Processing - https://www.edyoda.com/resources/videolisting/1419/
GAN Miniseries - https://www.edyoda.com/resources/videolisting/1418/
Videos from deep cognition studio - https://www.edyoda.com/resources/dashboard/deepcognition/

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