Applied Machine Learning Solutions with Python: Production-ready ML Projects Using Cutting-edge Libraries and Powerful Statistical Techniques Paperback – 31 August 2021

A problem-focused guide for tackling industrial machine learning issues with methods and frameworks chosen by experts.Description
This book discusses how to apply machine learning to real-world problems by utilizing real-world data. In this book, you will investigate data sources, become acquainted with data pipelines, and practice how machine learning works through numerous examples and case studies.

The book begins with high-level concepts and implementation (with code!) and progresses towards the real-world of ML systems. It briefly discusses various concepts of Statistics and Linear Algebra.What you will learn
● Construct a machine learning problem, evaluate the feasibility, and gather and clean data.
● Learn to explore data first, select, and train machine learning models.Who this book is for
This book caters to beginners in machine learning, software engineers, and students who want to gain a good understanding of machine learning concepts and create production-ready ML systems. This book assumes you have a beginner-level understanding of Python.Table of Contents
1. Introduction to Machine Learning
2. Problem Formulation in Machine Learning
3. Data Acquisition and Cleaning
4. Exploratory Data Analysis
5. Model Building and Tuning
6. Taking Our Model into Production
7. Data Analytics Use Case
8. Building a Custom Image Classifier from Scratch
9. Building a News Summarization App Using Transformers
10. Multiple Inputs and Multiple Output Models
11. Contributing to the Community
12. Creating Your Project
13. Crash Course in Numpy, Matplotlib, and Pandas
14. Crash Course in Linear Algebra and Statistics
15. Crash Course in FastAPIAbout the Authors
Siddhanta Bhatta is a Machine Learning engineer with 6 years of experience in building machine learning products.