English | 2022 | ISBN: B09PR53PND | 51 Pages | EPUB, AZW, PDF | 2 MB
Machine Learning (ML) is that field of computer science with the help of which computer systems can provide sense to data in much the same way as human beings do.
In simple words, ML is a type of artificial intelligence that extracts patterns out of raw data by using an algorithm or method. The key focus of ML is to allow computer systems to learn from experience without being explicitly programmed or human intervention.
The first part of this book introduces Python basics including
Data Structures like Pandas
Foundational libraries like Numpy, Seaborn, and Scikit-Learn
The second part of this book shows you how to build predictive machine learning models step by step using techniques such as
Regression analysis
Decision tree analysis
Training and testing data models
Tensor Flow, Keras, and PyTorch
Additional data science concepts like Classification Analysis, Clustering, Association Learning, and Dimension Reduction
The final part of the book provides a structured framework on how to solve real-world problems using data science and how to structure your data science project.
After reading this book you will be able to
Code in Python with confidence
Build new machine learning models from scratch
Know how to clean and prepare your data for analytics
Speak confidently about statistical analysis techniques
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