Machine learning and artificial intelligence (AI) have become ubiquitous in our everyday lives. Wherever we go, whatever we do, we are constantly interacting with AI in one way or another. And neural networks and deep learning are driving these AI advances. Powered by neural networks, AI systems are now able to achieve human-like performance in many areas.
This book provides you with the opportunity to create six different neural network projects from scratch. Through these projects, you will have the opportunity to create some of the AI systems that we commonly see today, including face recognition, sentiment analysis, and medical diagnosis. In each project, we'll provide a problem statement, the specific neural network architecture to be used to tackle that problem, the reasoning for the choice of neural network used, and the Python code to implement the given solution from scratch.
By the end of the book, you will be well versed in the different neural network architectures, having created cutting edge AI projects in Python that will immediately strengthen your machine learning portfolio.
