Machine Learning and Deep Learning are growing at a faster pace. According to MIT, in the upcoming future, about 8.5 out of every 10 sectors will be somehow based on AI. And if you are the one who is looking to get in this field or have a basic understanding of it and want to be an expert “Machine Learning Yearning” a book by Andrew Y. Ng is your key.

Andrew Y. Ng is a prestige name in the field of machine learning. He is a co-founder of Coursera, associate professor at Stanford University’s Computer Science and EE departments, Baidu’s Chief Scientist and a former head of Google Brain.

Machine Learning Yearning is the current work of Andrew Ng to teach students how to structure machine learning projects.

Machine Learning Yearning provides guidelines to machine learning practitioners (developers and managers) to help them make decisions related to design, data collection, debugging, etc. It introduces just the necessary background, provides best practices and common pitfalls with case studies.

Machine Learning Yearning broadly focuses on teaching how to make ML algorithms work in a more efficient and less time-consuming manner and how to structure machine learning projects. Andrew Ng’s book has also mentioned some AI classes that will give you a hammer, but it also teaches you how to use the hammer.

The major concepts that Andrew Ng covers in Machine Learning Yearning are how to prioritize the most promising directions for an AI project, diagnose errors in a machine learning system, build ML in complex settings, such as mismatched training/test set. Machine Learning Yearning also covers how to set up an ML project to compare to and/or surpass the human-level performance, know when and how to apply end-to-end learning, transfer learning, and multi-task learning.

The specialty of Andrew Ng books are they always appear simple and anyone can quickly understand it. Machine Learning Yearning also follows the same style of Andrew Ng’s books.

Machine Learning Yearning is not a book that came wrapped with lots of machine learning mathematics. It is a book that can fit anyone who has a basic understanding of machine learning and what it actually does, having a piece of good knowledge about the programming language that he will use for ML will really help him to absorb Machine Learning Yearning fastly. Machine Learning Yearning is also very helpful for data scientists to understand how to set technical directions for a machine learning project.

This book covered the following topics in this guide for the Business Strategy:

1. Data Science Process
2. Data Visualization in Business
3. Understand How to answer Why
4. Know ML Key Terminology
5. Understand ML Implementation
6. ML Applications on Marketing and Retail

More about author Andrew Ng:

Andrew Ng was born in London in the UK in 1976. His parents were both from Hong Kong. He spent time in Hong Kong and Singapore and later graduated from Raffles Institution in Singapore in 1992. In 1997, he received his undergraduate degree with a triple major in computer science, statistics, and economics at the top of his class from Carnegie Mellon University in Pittsburgh, Pennsylvania. Andrew Ng earned his master’s degree from the Massachusetts Institute of Technology in Cambridge, Massachusetts in 1998 and received his Ph.D. from the University of California, Berkeley in 2002. He started working at Stanford University in 2002. He currently lives in Los Altos Hills, California.  MIT Tech Review named them an AI power couple.

Ng researches primarily in machine learning and deep learning and is one of the world’s most famous computer scientists. His early work includes the Stanford Autonomous Helicopter project, which developed one of the most capable autonomous helicopters in the world, and the STAIR (Stanford Artificial Intelligence Robot) project, which resulted in ROS, a widely used open-source robotics software platform. In 2011, Ng founded the Google Brain project at Google, which developed large-scale artificial neural networks using Google’s distributed computing infrastructure.

Download here

Ryan Hoang
Theo Techgrabyte, Amazon

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