TENSORFLOW MACHINE LEARNING: 3 in 1- Beginner’s Guide+ Simple and Effective Tips and Tricks+ Advanced Guide to Learn Machine Learning With Scikit-Learn, Keras and TensorFlow
While TensorFlow is an incredibly important machine and deep learning library, we also give you an introduction to three others – NumPy, Pandas, and Scikit Learn. I have produced a hands-on guide, with plenty of code examples for you to follow along with
Here’s what you will learn:
- What deep learning is
- The difference between deep learning and machine learning
- What TensorFlow is
- How to install it on Windows and Mac
- The basics of TensorFlow
- Using TensorBoard
- About NumPy, Scikit Learn, and Pandas
- About linear regression
- Kernel methods
- Building an Artificial Neural Network using TensorFlow
- TensorFlow image classification
- TensorFlow autoencoders
- Much more
If you are already proficient at programming in Python and are ready to take the next step into machine learning, this guide is for you. Scroll up, hit that Buy Now button, and set off on a brand new machine learning journey.
Have you ever wondered how machine learning works? These days, machine learning, deep learning and neural nets are common terms and they are here to stay as a part of our everyday language. Machine learning is not the easiest of topics to teach, purely because there is so much to it.
Machine learning, deep learning and artificial intelligence are used in more applications than most humans even think about – email, Amazon, Netflix, Spotify, and other popular online marketplaces use machine learning to weed out spam emails and bring you recommendations based on your shopping or streaming preferences. Machine learning is used in healthcare, in finance, in just about every industry you can think of – it’s here to stay, whether we like it or not.
One of the most important parts of learning machine learning is knowing which algorithm to choose and which library. Python is the most popular machine learning programming language and it has a huge advantage over other languages – the large amount of built-in libraries; three of the most important are TensorFlow, Keras and Scikit-Learn.
And that’s what this book is about – machine learning with TensorFlow, Keras and Scikit-learn. Here’s what you will learn:
- What machine learning is
- How it applies in the real world
- Different models and learning types
- Different machine learning algorithms
- Deep learning vs. machine learning
- What TensorFlow is and how to use it
- What TensorFlow comprises
- Operators, variables, placeholders, and more
- What Keras is and how to use it
- Keras vs. TensorFlow
- How to use Keras for linear regression
- How to use Keras to build a neural net
- What Scikit-Learn is and how to use it
- Using Scikit-Learn to build regression and classification trees
- How to build a random forest model
- How to install Keras, TensorFlow and Scikit-Learn
- And much more!
All the practical examples in the book use Python, so you are expected to need some knowledge of the language before you start. If you’re looking to advanced your skills in machine learning, then this is the book for you! Grab your copy of this book today!