Bharath Ramsundar – författare

Learn how to solve challenging machine learning problems with TensorFlow, Google’s revolutionary new software library for deep learning. If you have some background in basic linear algebra and calculus, this practical book introduces machine-learning fundamentals by showing you how to design systems capable of detecting objects in images, understanding text, analyzing video, and predicting the properties of potential medicines.

TensorFlow for Deep Learning teaches concepts through practical examples and helps you build knowledge of deep learning foundations from the ground up. It’s ideal for practicing developers with experience designing software systems, and useful for scientists and other professionals familiar with scripting but not necessarily with designing learning algorithms.

Learn TensorFlow fundamentals, including how to perform basic computationBuild simple learning systems to understand their mathematical foundationsDive into fully connected deep networks used in thousands of applicationsTurn prototypes into high-quality models with hyperparameter optimizationProcess images with convolutional neural networksHandle natural language datasets with recurrent neural networksUse reinforcement learning to solve games such as tic-tac-toeTrain deep networks with hardware including GPUs and tensor processing units

Learn how to solve challenging machine learning problems with TensorFlow, Google’s revolutionary new software library for deep learning. If you have some background in basic linear algebra and calculus, this practical book introduces machine-learning fundamentals by showing you how to design systems capable of detecting objects in images, understanding text, analyzing video, and predicting the properties of potential medicines.

TensorFlow for Deep Learning teaches concepts through practical examples and helps you build knowledge of deep learning foundations from the ground up. It’s ideal for practicing developers with experience designing software systems, and useful for scientists and other professionals familiar with scripting but not necessarily with designing learning algorithms.

Learn TensorFlow fundamentals, including how to perform basic computationBuild simple learning systems to understand their mathematical foundationsDive into fully connected deep networks used in thousands of applicationsTurn prototypes into high-quality models with hyperparameter optimizationProcess images with convolutional neural networksHandle natural language datasets with recurrent neural networksUse reinforcement learning to solve games such as tic-tac-toeTrain deep networks with hardware including GPUs and tensor processing units

Learn how to solve challenging machine learning problems with TensorFlow, Google’s revolutionary new software library for deep learning. If you have some background in basic linear algebra and calculus, this practical book introduces machine-learning fundamentals by showing you how to design systems capable of detecting objects in images, understanding text, analyzing video, and predicting the properties of potential medicines. TensorFlow for Deep Learning teaches concepts through practical examples and helps you build knowledge of deep learning foundations from the ground up. It’s ideal for practicing developers with experience designing software systems, and useful for scientists and other professionals familiar with scripting but not necessarily with designing learning algorithms. Learn TensorFlow fundamentals, including how to perform basic computation Build simple learning systems to understand their mathematical foundations Dive into fully connected deep networks used in thousands of applications Turn prototypes into high-quality models with hyperparameter optimization Process images with convolutional neural networks Handle natural language datasets with recurrent neural networks Use reinforcement learning to solve games such as tic-tac-toe Train deep networks with hardware including GPUs and tensor processing units

Deep learning has already achieved remarkable results in many fields. Now it’s 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. You’ll follow a case study on the problem of designing new therapeutics that ties together physics, chemistry, biology, and medicine—an example that represents one of science’s 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 it’s working

Deep learning has already achieved remarkable results in many fields. Now it’s 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. You’ll follow a case study on the problem of designing new therapeutics that ties together physics, chemistry, biology, and medicine—an example that represents one of science’s 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 it’s working