دانلود کتاب یادگیری عمیق با پایتون

If you’ve picked up this book, you’re probably aware of the extraordinary progress that deep learning has represented for the field of artificial intelligence in the recent past. We went from near-unusable computer vision and natural language processing to highly performant systems deployed at scale in products you use every day. The consequences of this sudden progress extend to almost every industry. We’re already applying deep learning to an amazing range of important problems across domains as different as medical imaging, agriculture, autonomous driving, education, disaster prevention, and manufacturing. Yet, I believe deep learning is still in its early days. It has only realized a small fraction of its potential so far. Over time, it will make its way to every problem where it can help—a transformation that will take place over multiple decades. In order to begin deploying deep learning technology to every problem that it could solve, we need to make it accessible to as many people as possible, including non-experts—people who aren’t researchers or graduate students. For deep learning to reach its full potential, we need to radically democratize it. And today, I believe that we’re at the cusp of a historical transition, where deep learning is moving out of academic labs and the R&D departments of large tech companies to become a ubiquitous part of the toolbox of every developer out there—not unlike the trajectory of web development in the late 1990s. Almost anyone can now build a website or web app for their business or community of a kind that would have required a small team of specialist engineers in 1998. In the not-so-distant future, anyone with an idea and basic coding skills will be able to build smart applications that learn from data.