Python Machine Learning For Beginners 2021: Machine Learning

We live in a world of data deluge where gigabytes of data are generated daily. It is possible that this data might not be very useful for our daily applications. Major setbacks in the use of such data may be due to the presence of loopholes in data links previously generated or the data might be too vast for the limited human mind. Machine learning in this book presents some of the solutions to the problems above. Being an introductory guide, expect to learn the various basics involved in Machine Learning and Python. This book provides an insight into the new world of big data, then behooves you to learn more about Machine Learning.

With a detailed and concise overview of the fundamentals, along with the challenges and limitations currently being tackled by the pros, inside this comprehensive guide you will

-Learn the Fundamentals of Machine Learning which Are Being Developed and Advanced with Python

-What is Machine Learning and how it is applied in real-world situations

-Algorithms, in a Language that Requires No Prior Background in Python

-Discover best practices for evaluating and tuning models

-Discover the Details of the Supervised, Unsupervised, and Reinforcement Algorithms, which Serve as the Skeleton of Hundreds of Machine Learning Algorithms Being Developed Every Day

-Become Familiar with Data Science Technology, an Umbrella Term Used for the Cutting-Edge Technologies of Today

-Understand the Entire Process of Creating Neural Network Models on TensorFlow, Using Open Source Data Sets and real Python Code

-Uncover the Secrets of the Most Critical Aspect of Developing a Machine Learning Model - Data Pre-Processing and Training/Testing Subsets

-Artificial Neural Networks

-And Much More

So what are you waiting for?

Even if some concepts of Machine Learning algorithms can appear complex to most computer programming beginners, this book takes the time to explain them in a simple and concise way.

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