Data Science and Machine Learning with Python - Hands On!

Description

In this course, you will learn :

• Regression analysis.
• K-Means Clustering.
• Principal Component Analysis.
• Train/Test and cross validation.
• Bayesian Methods.
• Decision Trees and Random Forests.
• Multivariate Regression.
• Multi-Level Models.
• Support Vector Machines.
• Reinforcement Learning.
• Collaborative Filtering.
• K-Nearest Neighbor.
• Bias/Variance Tradeoff.
• Ensemble Learning.
• Term Frequency / Inverse Document Frequency.
• Experimental Design and A/B Tests.