A deep learning library in Python, Keras is an API designed to minimise the number of user actions required for common use cases. It is one of the most used deep learning frameworks among developers and finds a way to popularity because of its ease to run new experiments, is fast and empowers to explore a lot of ideas. Built on top of TensorFlow 2.0, Keras is an industry-strength framework that can scale to large clusters of GPUs or an entire TPU pod. 

There is no denying that Keras has been used extensively in machine learning workflow from data management to hyperparameter training to deployment solutions. Its ease-of-use makes it a deep learning solution of choice amid researchers, professionals and students alike. 

Here we list 8 free resources which will help you get hands-on exposure to one of the most popular libraries.  

1| Introduction to Keras for Engineers: This online blog by F Chollet, the creator of Keras, is the best way to get started with the library. In this blog, he explains the nitty-gritty of using Keras to build real-world machine learning solutions. It is highly useful for machine learning engineers who are looking to use Keras to build real deep-learning powered products. The guide serves as the first introduction to core Keras API concepts. A similar guide is available for machine learning researchers which helps with more complex applications in computer vision and NLP. 

2| Learn through codes on GitHub: It is one of the best options to learn Keras for free by trying reverse engineering through sample codes on GitHub. This directory of tutorials and open-source code repositories by F Chollet helps in working with Keras, the Python deep learning library. 

3| Deep Learning Fundamentals with Keras by edX: This free course offered by IBM is best for someone new to deep learning. It gives an introduction to the field, eventually helping to develop your first deep learning library using Keras. It covers some of the exciting applications of deep learning, basics of neural networks, building deep learning models and more. It gives detailed insight into how to build Keras, train and test deep learning models. While the course is free, it provides an option to get a verified certificate which is paid. 

4| Advanced Deep Learning with Keras by Datacamp: This course provides an overview of solving a wide range of problems using Keras functional API. Starting with simple, multi-layer networks, it progresses to more complicated architectures. It covers how to build models with multiple inputs and a single output. It also covers advanced topics such as category embeddings and multiple-output networks. The first session on the Keras Functional API is free which covers the basics of the Keras functional API. It includes building a simple functional network using functional building blocks, fitting it to data, and making predictions.

5| Introduction to Deep Learning & Neural Networks with Keras by Coursera: This free course covers an introduction to the field of deep learning and building deep learning models. On completion of this course, learners will be able to describe neural networks, understand unsupervised deep learning models such as autoencoders, understand supervised deep learning models, build deep learning models and networks using the Keras library, and more. 

6| Applied AI with DeepLearning By Coursera: This advanced course offered as a part of the IBM Advanced Data Science Certificate gives access to insights into Deep Learning models used by experts in NLP, Computer Vision, Time Series Analysis, and many other disciplines. After learning the fundamentals of Linear Algebra and Neural Networks, the course takes through popular deep learning frameworks such as Keras, TensorFlow, PyTorch, DeepLearning4J and Apache SystemML, with Keras making up for the most of the course. 

7| Learn Keras: Build 4 Deep Learning Applications by Udemy: This free course by Udemy covers the implementation of CNN, deep neural networks, understanding of Keras syntax, understanding of different deep learning algorithms and more. It is designed to get acquainted with deep learning using Keras. The course covers different machine learning algorithms and their use cases. 

8| Youtube tutorial by Edureka: This free tutorial on Youtube helps to get started with Keras. Aimed for beginners, the video runs through creating deep learning models using Keras in Python. This quick and insightful tutorial covers the basics of working of Keras along with interesting use cases.