Machine Learning Algorithms
Machine learning explores the study and construction of algorithms that can learn from, and make predictions on, data. This book will act as an entry point for anyone who wants to make a career in the field of Machine Learning. A few famous algorithms that are covered in this book are Linear regression, Logistic Regression, SVM, Naïve Bayes, K-Means, Random Forest, TensorFlow, and Feature engineering.
Offered by
Difficulty Level
Intermediate
Completion Time
12h
Language
English
About Book
Who Is This Book For?
This book is for IT professionals who want to enter the field of data science and are very new to Machine Learning. Familiarity with languages such as R and Python will be invaluable here.
Machine Learning Algorithms
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 12h total length
Gentle Introduction To Machine Learning
Important Elements In A Machine Learning
Feature Selection & Feature Engineering
Linear Regression
Logistic Regression
Naïve Baiyes
Support Vector Machines
Decision Trees And Random Forests
K-Means
Heirarchical Clustering
Introduction To Recommedation Systems
Introduction To Natural Language Processing
Topic Modelling and Sentiment Analysis in NLP
Brief Introduction To Deep Learning And Tensorflow
Creating a Machine Learning Architecture
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