Time to flex your machine learning muscles! Take on the carefully designed challenges of the Machine Learning Bookcamp and master essential ML techniques through practical application.
In Machine Learning Bookcamp you will:
•Collect and clean data for training models
•Use popular Python tools, including NumPy, Scikit-Learn, and TensorFlow
•Apply ML to complex datasets with images
•Deploy ML models to a production-ready environment
The only way to learn is to practice! In Machine Learning Bookcamp, you’ll create and deploy Python-based machine learning models for a variety of increasingly challenging projects. Taking you from the basics of machine learning to complex applications such as image analysis, each new project builds on what you’ve learned in previous chapters. You’ll build a portfolio of business-relevant machine learning projects that hiring managers will be excited to see.
about the technology
Master key machine learning concepts as you build actual projects! Machine learning is what you need for analyzing customer behavior, predicting price trends, evaluating risk, and much more. To master ML, you need great examples, clear explanations, and lots of practice. This book delivers all three!
about the book
Machine Learning Bookcamp presents realistic, practical machine learning scenarios, along with crystal-clear coverage of key concepts. In it, you’ll complete engaging projects, such as creating a car price predictor using linear regression and deploying a churn prediction service. You’ll go beyond the algorithms and explore important techniques like deploying ML applications on serverless systems and serving models with Kubernetes and Kubeflow. Dig in, get your hands dirty, and have fun building your ML skills!
What's inside
Collect and clean data for training models
Use popular Python tools, including NumPy, Scikit-Learn, and TensorFlow
Deploy ML models to a production-ready environment
About the reader
Python programming skills assumed. No previous machine learning knowledge is required.
About the author
Alexey Grigorev is a principal data scientist at OLX Group. He runs DataTalks.Club, a community of people who love data.
Table of Contents
1 Introduction to machine learning
2 Machine learning for regression
3 Machine learning for classification
4 Evaluation metrics for classification
5 Deploying machine learning models
6 Decision trees and ensemble learning
7 Neural networks and deep learning
8 Serverless deep learning
9 Serving models with Kubernetes and Kubeflow
Ebook License
End-User Warranty And License Agreement
1. Grant Of License
Manning Has Authorized The Download By You Of An Unrestricted Number Of Copies Of The Electronic Book (Ebook) In Any Of The Available Formats. Manning Grants You A Nonexclusive, Nontransferable License To Use The Ebook According To The Terms And Conditions Herein. This License Agreement Permits You To Install The Ebook On Any And All Your Devices For Your Personal Use Only.
2. Restrictions
You Shall Not: (1) Share, Resell, Rent, Assign, Timeshare, Distribute, Or Transfer All Or Part Of The Ebook Or Any Rights Granted Hereunder To Any Other Person; (2) Duplicate The Ebook, Except For A Single Backup Or Archival Copy; (3) Remove Any Proprietary Notices, Labels, Or Marks From The Ebook; (4) Transfer Or Sublicense Title To The Ebook To Any Other Party.
3. Intellectual Property Protection
The Ebook Is Owned By Manning And Is Protected By United States And International Copyright And Other Intellectual Property Laws. Manning Reserves All Rights In The Ebook Not Expressly Granted Herein. This License And Your Right To Use The Ebook Terminate Automatically If You Violate Any Part Of This Agreement. In The Event Of Termination, You Must Remove The Original And Any Copies Of The Ebook From All Your Devices.
4. Source Code Supplementary Material
Any Source Code Files Provided As A Supplement To The Book Are Freely Available To The Public For Download. Reuse Of The Code Is Permitted, In Whole Or In Part, Including The Creation Of Derivative Works, Provided That You Acknowledge That You Are Using It And Identify The Source: Title, Publisher And Year.
5. Limited Warranty
Manning Warrants That The Ebook Files, A Copy Of Which You Are Authorized To Download, Are Free From Defects In The Operational Sense That They Can Be Read By A Pdf Reader Or Epub Reader, Or Other. Except For This Express Limited Warranty, Manning Makes And You Receive No Warranties, Express, Implied, Statutory Or In Any Communication With You, And Manning Specifically Disclaims Any Other Warranty Including The Implied Warranty Of Merchantability Or Fitness Or A Particular Purpose. Manning Does Not Warrant That The Operation Of The Ebook Will Be Uninterrupted Or Error Free. If The Ebook Was Purchased In The United States, The Above Exclusions May Not Apply To You As Some States Do Not Allow The Exclusion Of Implied Warranties. In Addition To The Above Warranty Rights, You May Also Have Other Rights That Vary From State To State.
6. Limitation Of Liability
In No Event Will Manning Be Liable For Any Damages, Whether Arising For Tort Or Contract, Including Loss Of Data, Lost Profits, Or Other Special, Incidental, Consequential, Or Indirect Damages Arising Out Of The Use Or Inability To Use The Ebook.
7. General
This Agreement Constitutes The Entire Agreement Between You And Manning And Supersedes Any Prior Agreement Concerning The Ebook. This Agreement Is Governed By The Laws Of The State Of New York
