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TORRENT DETAILS

[DesireCourse.Com] Udemy - Data Science Supervised Machine Learning In Python

TORRENT SUMMARY

	Status:	All the torrents in this section have been verified by our verification system
Category:	Other
Infohash	b4133b518fb1daf9fdd1eedfc8fd67ff4ca4963d
Size:	409.3 MB in 39 files
Release Date(s):	Torrent Release: 26-12-2018 by user
Swarm:	0 Seeds & 0 Peers
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DESCRIPTION

Data Science: Supervised Machine Learning in Python

Full Guide to Implementing Classic Machine Learning Algorithms in Python and with Sci-Kit Learn

For More Courses Visit: https://desirecourse.com

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FILE LIST

Filename		Size
	01 Introduction and Review/001 Introduction and Outline.mp4	7.6 MB
	01 Introduction and Review/002 Review of Important Concepts.mp4	6 MB
	01 Introduction and Review/003 Where to get the Code and Data.mp4	3.9 MB
	01 Introduction and Review/004 How to Succeed in this Course.mp4	8.8 MB
	02 K-Nearest Neighbor/005 K-Nearest Neighbor Concepts.mp4	8.6 MB
	02 K-Nearest Neighbor/006 KNN in Code with MNIST.mp4	18 MB
	02 K-Nearest Neighbor/007 When KNN Can Fail.mp4	7.7 MB
	02 K-Nearest Neighbor/008 KNN for the XOR Problem.mp4	4.3 MB
	02 K-Nearest Neighbor/009 KNN for the Donut Problem.mp4	5.4 MB
	03 Naive Bayes and Bayes Classifiers/010 Naive Bayes.mp4	15.7 MB
	03 Naive Bayes and Bayes Classifiers/011 Naive Bayes Handwritten Example.mp4	5.8 MB
	03 Naive Bayes and Bayes Classifiers/012 Naive Bayes in Code with MNIST.mp4	14.4 MB
	03 Naive Bayes and Bayes Classifiers/013 Non-Naive Bayes.mp4	7.3 MB
	03 Naive Bayes and Bayes Classifiers/014 Bayes Classifier in Code with MNIST.mp4	4.4 MB
	03 Naive Bayes and Bayes Classifiers/015 Linear Discriminant Analysis LDA and Quadratic Discriminant Analysis QDA.mp4	10.3 MB
	03 Naive Bayes and Bayes Classifiers/016 Generative vs Discriminative Models.mp4	5.1 MB
	04 Decision Trees/017 Decision Tree Basics.mp4	8.3 MB
	04 Decision Trees/018 Information Entropy.mp4	7 MB
	04 Decision Trees/019 Maximizing Information Gain.mp4	14 MB
	04 Decision Trees/020 Choosing the Best Split.mp4	6.7 MB
	04 Decision Trees/021 Decision Tree in Code.mp4	30.3 MB
	05 Perceptrons/022 Perceptron Concepts.mp4	12.2 MB
	05 Perceptrons/023 Perceptron in Code.mp4	13.8 MB
	05 Perceptrons/024 Perceptron for MNIST and XOR.mp4	8.7 MB
	05 Perceptrons/025 Perceptron Loss Function.mp4	6.9 MB
	06 Practical Machine Learning/026 Hyperparameters and Cross-Validation.mp4	7.4 MB
	06 Practical Machine Learning/027 Feature Extraction and Feature Selection.mp4	7.1 MB
	06 Practical Machine Learning/028 Comparison to Deep Learning.mp4	8.7 MB
	06 Practical Machine Learning/029 Multiclass Classification.mp4	5.7 MB
	06 Practical Machine Learning/030 Sci-Kit Learn.mp4	15.8 MB
	06 Practical Machine Learning/031 Regression with Sci-Kit Learn is Easy.mp4	10.7 MB
	07 Building a Machine Learning Web Service/032 Building a Machine Learning Web Service Concepts.mp4	7.2 MB
	07 Building a Machine Learning Web Service/033 Building a Machine Learning Web Service Code.mp4	11.9 MB
	08 Conclusion/034 Whats Next Support Vector Machines and Ensemble Methods e.g. Random Forest.mp4	6.3 MB
	09 Appendix/035 How to install Numpy Scipy Matplotlib and Sci-Kit Learn.mp4	43.9 MB
	09 Appendix/036 How to Code by Yourself part 1.mp4	24.5 MB
	09 Appendix/037 How to Code by Yourself part 2.mp4	14.8 MB
	09 Appendix/038 Where to get Udemy coupons and FREE deep learning material.mp4	4 MB
	[DesireCourse.Com].txt	754 B

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