Programming Neural Networks with Python

Neural networks are at the heart of AI—so ensure you’re on the cutting edge with this guide. For true beginners, get a crash course in Python and the mathematical concepts you’ll need to understand and create neural networks. Or jump right into programming your first neural network, from implementing the scikit-learn library to using the perceptron learning algorithm. Learn how to train your neural network, measure errors, make use of transfer learning, implementing the CRISP-DM model, and more. Whether you’re interested in machine learning, gen AI, LLMs, deep learning, or all of the above, this is the AI book you need. Highlights include: 1) Network creation 2) Network training 3) Supervised and unsupervised learning 4) Reinforcement learning 5) Algorithms 6) Multi-layer networks 7) Deep neural networks 8) Back propagation 9) Transformers 10) Python 11) Mathematical concepts 12) TensorFlow.