Andrew Trask is a PhD student at Oxford University and a research scientist at DeepMind. Previously, Andrew was a researcher and analytics product manager at Digital Reasoning, where he trained the world's largest artificial neural network and helped guide the analytics roadmap for the Synthesys cognitive computing platform.
Grokking Deep Learning
Par :Formats :
- Nombre de pages309
- FormatGrand Format
- PrésentationBroché
- Poids0.615 kg
- Dimensions18,4 cm × 23,3 cm × 2,5 cm
- ISBN978-1-61729-370-2
- EAN9781617293702
- Date de parution15/05/2019
- ÉditeurManning
Résumé
Deep learning, a branch of artificial intelligence, teaches computers to learn by using neural networks, technology inspired by the human brain. Online text translation, self-driving cars, personalized product recommendations, and virtual voice assistants are just a few of the exciting modern advancements possible thanks to deep learning. Grokking Deep Learning teaches you to build deep learning neural networks from scratch ! In his engaging style, seasoned deep learning expert Andrew Trask shows you the science under the hood, so you grok for yourself every detail of training neural networks.
Using only Python and its math-supporting library, NumPy, you'll train your own neural networks to see and understand images, translate text into different languages, and even write like Shakespeare ! When you're done, you'll be fully prepared to move on to mastering deep learning frameworks. What's Inside : The science behind deep learning ; Building and training your own neural networks ; Privacy concepts, including federated learning ; Tips for continuing your pursuit of deep learning.
For readers with high school-level math and intermediate programming skills.
Using only Python and its math-supporting library, NumPy, you'll train your own neural networks to see and understand images, translate text into different languages, and even write like Shakespeare ! When you're done, you'll be fully prepared to move on to mastering deep learning frameworks. What's Inside : The science behind deep learning ; Building and training your own neural networks ; Privacy concepts, including federated learning ; Tips for continuing your pursuit of deep learning.
For readers with high school-level math and intermediate programming skills.