MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 1.5 Hours | 340 MB
Genre: eLearning | Language: English
Scikit-learn has evolved as a robust library for Machine Learning applications in Python with support for a wide range of Supervised and Unsupervised Learning Algorithms.
With this course you will learn the Decision Tree algorithms and Ensemble Models to build Random Forest, Regression Analysis. You will focus on Decision Trees and Ensemble Algorithms. Moving forward, you learn to use scikit-learn to classify text and Multiclass with scikit-learn. You will explore various algorithms for classification. You will also look at Naive Bayes model and Label Propagation. Finally, you'll use Neural Networks using different Classifiers and create your own Simple Estimator.
Create_Your_Own_Sophisticated_Model_with_Neural_Networks__Video_.part2.rar - 100.0 MB
Create_Your_Own_Sophisticated_Model_with_Neural_Networks__Video_.part3.rar - 100.0 MB
Create_Your_Own_Sophisticated_Model_with_Neural_Networks__Video_.part4.rar - 40.5 MB
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