<p>This course is for you if you are new to Machine Learning but want to learn it without all the math. This course is also for you if you have tried to use a machine learning course but could never figure out how to use it to solve your own problems.<br />In this course, we will start from scratch. So we will immediately start coding even before installation! You will see a brief bit of absolutely essential theory and then we will get into environment setup and explain almost all concepts through code. You will be using Keras, one of the easiest and most powerful machine learning tools out there.</p> <p>You will start with a basic model of how machines learn and then move on to higher models, such as:</p> <ul> <li>Convolutional Neural Networks&nbsp;</li> <li>Residual connections&nbsp;</li> <li>Google's Inception Module</li> </ul> <p>All this with only a few lines of code. All the examples used in the course come with starter code which will get you started and without the hard work.</p> <p>All the code files are placed at&nbsp;<a href="https://github.com/PacktPublishing/-Practical-Deep-Learning-with-Keras-and-Python" target="_blank">https://github.com/PacktPublishing/-Practical-Deep-Learning-with-Keras-and-Python</a></p> <h1>Style and Approach</h1> <p>This course is based on a case study-based approach and explains why we need machine learning and how everything fits together.</p>