By Pratap Dangeti
- Learn in regards to the facts in the back of robust predictive types with p-value, ANOVA, and F- statistics.
- Implement statistical computations programmatically for supervised and unsupervised studying via K-means clustering.
- Master the statistical point of computer studying with the aid of this example-rich consultant to R and Python.
Complex data in desktop studying fear loads of builders. figuring out statistics is helping you construct robust desktop studying types which are optimized for a given challenge assertion. This ebook will train you all it takes to accomplish complicated statistical computations required for desktop studying. you'll achieve details on data at the back of supervised studying, unsupervised studying, reinforcement studying, and extra. comprehend the real-world examples that debate the statistical part of laptop studying and get yourself up to speed with it. additionally, you will layout courses for acting initiatives comparable to version, parameter becoming, regression, class, density assortment, and more.
By the tip of the booklet, you could have mastered the necessary data for computer studying and should have the capacity to practice your new talents to any kind of problem.
What you'll learn
- Understand the Statistical and laptop studying basics essential to construct models
- Understand the key ameliorations and parallels among the statistical approach and the desktop studying method to remedy problems
- Learn easy methods to organize facts and feed types by utilizing the proper laptop studying algorithms from the more-than-adequate R and Python packages
- Analyze the implications and music the version competently in your personal predictive goals
- Understand the suggestions of required records for computer Learning
- Introduce your self to priceless basics required for development supervised & unsupervised deep studying models
- Learn reinforcement studying and its program within the box of synthetic intelligence domain
About the Author
Pratap Dangeti develops desktop studying and deep studying ideas for established, snapshot, and textual content facts at TCS, analytics and insights, innovation lab in Bangalore. He has got loads of adventure in either analytics and information technological know-how. He got his master's measure from IIT Bombay in its business engineering and operations examine application. he's a man-made intelligence fanatic. whilst no longer operating, he loves to examine next-gen applied sciences and cutting edge methodologies.
Table of Contents
- Journey from information to desktop Learning
- Parallelism of records and laptop Learning
- Logistic Regression vs. Random Forest
- Tree-Based desktop studying models
- K-Nearest pals & Naive Bayes
- Support Vector Machines & Neural Networks
- Recommendation Engines
- Unsupervised Learning
- Reinforcement Learning
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Extra resources for Statistics for Machine Learning
Statistics for Machine Learning by Pratap Dangeti