Machine Learning Bookcamp

Build a Portfolio of Real-Life Projects

De: Alexey Grigorev

Narrado por: Adam Newmark

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.

Summary

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!

About the listener:

Python programming skills assumed. No previous ML 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.

PLEASE NOTE: When you purchase this title, the accompanying PDF will be available in your Audible Library along with the audio.

©2021 Manning Publications (P)2022 Manning Publications

Good but I mixed ebook + audio book

Since this is a very technical book, I bought the ebook as well, so I read it while listening.

I found is a good formula for this kind of content, the ebook has an AI assistant, through a LLM (I guess trained on the book’s and editorial content) helps to solve any question related with the book.

Good content, but audio book for me was not enough

Thank you!

My review may be biased.
I'm a slow reader and need this audio to speed up my reading.
The audiobook comes with a PDF file downable on Audible.com, but I still purchased a paper copy of this book to ease my studying. (and the result is great!)
The author is fantastic in producing visual illustrations to simplify math and logic learning.
My background is old school imperative Java/C programming and I benefit from these illustrations to adapt to vectorization programming paradigm.