Generative AI is the hottest topic in tech. This practical book teaches machine learning engineers and data scientists how to use TensorFlow and Keras to create impressive generative deep learning models from scratch, including variational autoencoders (VAEs), generative adversarial networks (GANs), Transformers, normalizing flows, energy-based models, and denoising diffusion models.

Easy to understand and engaging, this updated edition of Introducing Python is ideal for beginning programmers as well as those new to the language. Author Bill Lubanovic takes you from the basics to more involved and varied topics, mixing tutorials with cookbook-style code recipes to explain concepts in Python 3. End-of-chapter exercises help you practice what you've learned.

フレーゲからラッセル、そしてウィトゲンシュタインへ――二十世紀初頭、言葉についての問いと答えが重なりあい、つながりあっていった。天才たちの挑戦は言語哲学の源流を形作っていく。

No data is completely safe. Cyberattacks on companies and individuals are on the rise and growing not only in number but also in ferocity. And while you may think your company has taken all the precautionary steps to prevent an attack, no individual, company, or country is safe. Cybersecurity can no longer be left exclusively to IT specialists. Improving and increasing data security practices and identifying suspicious activity is everyone's responsibility, from the boardroom to the break room.

Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. With this practical book, you'll learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available through the framework of the data engineering lifecycle.