<p>The world has been obsessed with the terms machine learning and deep learning recently. We use these technologies every day with or without our knowledge through Google suggestions, translations, ads, movie recommendations, friend suggestions, and sales and customer experiences. There are tons of other applications too! No wonder that deep learning and machine learning specialists, along with data science practitioners, are the most sought-after talent in the technology world. However, it’s a common misconception that you need to study lots of mathematics, statistics, and complex algorithms for learning these technologies. It’s like believing that you must learn the working of a combustion engine before you learn how to drive a car. A basic know-how of the internal working of the engine is of course an added advantage, but it’s not mandatory.</p><p>Similarly, this course is a perfect balance between learning the basic deep learning concepts and implementing the built-in deep learning classes and functions from the Keras library using the Python programming language. These classes, functions and APIs are just like the control pedals of a car engine, which you can use to build an efficient deep-learning model. This is a basic-to-advanced crash course in deep learning, neural networks, and convolutional neural networks using Keras and Python. It’ll help your skill up to meet the demand of the tech world and skyrocket your career prospects.</p><p>All the code and supporting files for this course are available at https://github.com/PacktPublishing/Deep-Learning-and-Neural-Networks-using-Python---Keras-The-Complete-Beginners-Guide</p>