Bøker av Bharath Ramsundar

Deep learning has already achieved remarkable results in many fields. Now its making waves throughout the sciences broadly and the life sciences in particular. This practical book teaches developers and scientists how to use deep learning for genomics, chemistry, biophysics, microscopy, medical analysis, and other fields.Ideal for practicing developers and scientists ready to apply their skills to scientific applications such as biology, genetics, and drug discovery, this book introduces several deep network primitives. Youll follow a case study on the problem of designing new therapeutics that ties together physics, chemistry, biology, and medicinean example that represents one of sciences greatest challenges.Learn the basics of performing machine learning on molecular dataUnderstand why deep learning is a powerful tool for genetics and genomicsApply deep learning to understand biophysical systemsGet a brief introduction to machine learning with DeepChemUse deep learning to analyze microscopic imagesAnalyze medical scans using deep learning techniquesLearn about variational autoencoders and generative adversarial networksInterpret what your model is doing and how its working

Learn how to solve challenging machine learning problems with Tensorflow, Googles revolutionary new system for deep learning. If you have some background with basic linear algebra and calculus, this practical book shows you how to buildand when to usedeep learning architectures. Youll learn how to design systems capable of detecting objects in images, understanding human speech, analyzing video, and predicting the properties of potential medicines.TensorFlow for Deep Learning teaches concepts through practical examples and builds understanding of deep learning foundations from the ground up. Its ideal for practicing developers comfortable with designing software systems, but not necessarily with creating learning systems. This book is also useful for scientists and other professionals who are comfortable with scripting, but not necessarily with designing learning algorithms.Gain in-depth knowledge of the TensorFlow API and primitives.Understand how to train and tune machine learning systems with TensorFlow on large datasets.Learn how to use TensorFlow with convolutional networks, recurrent networks, LSTMs, and reinforcement learning.