Deep Learning with Python: From Neural Networks Fundamentals to Generative AI Applications
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كتاب Deep Learning With Python From Neural Networks Fundamentals To Generative Ai Applications
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Deep Learning With Python: From Neural Networks Fundamentals To Generative AI Applications
| مؤلف: | Mohammad Belal Ansari |
| قسم: | لغة برمجة بايثون Python [تعديل] |
| اللغة: | الإنجليزية |
| ترتيب الشهرة: | 1,078,874 رقم 1 هو الأشهر ! |
| رابط مختصر: | نسخ |
| المزيد من الكتب مثل هذا الكتاب | |
Mohammad Belal Ansari
Author, Researcher and Entrepreneur
الناشر والمؤلف
كتاب Deep Learning with Python: From Neural Networks Fundamentals to Generative AI Applications .
Mohammad Belal Ansari is an independent researcher, science writer, and entrepreneur with a strong interest in physics, cosmology, climate technology, and emerging scientific ideas. He holds a Master's degree in Physics and is passionate about making complex scientific concepts accessible to a wider audience.
His work explores some of the most profound questions in modern science, including the nature of time, relativity, quantum mechanics, black holes, consciousness, and the future of the universe. Through his writing, he aims to bridge the gap between advanced scientific research and curious readers seeking to understand the mysteries of reality.
In addition to his work as an author, Mohammad Belal Ansari is the founder of Ecoso Next Generation Pvt. Ltd., a climate-tech venture focused on innovative approaches to carbon capture and sustainable technologies.
He believes that science is not merely a collection of facts but a journey of discovery that expands our understanding of the universe and our place within it.
When he is not writing or researching, he explores new ideas at the intersection of physics, technology, environment, and innovation.
وصف الكتاب
Book Description
Unlock the power of artificial intelligence with Deep Learning with Python: From Neural Networks Fundamentals to Generative AI Applications, a practical and comprehensive guide designed for students, researchers, developers, and technology enthusiasts.
This book takes you on a step-by-step journey through the world of deep learning, starting with the fundamentals of artificial neural networks and progressing to advanced topics such as convolutional neural networks, transformer architectures, large language models, generative AI, multimodal systems, and reinforcement learning.
Using clear explanations, real-world examples, and hands-on Python code, you will learn how to build, train, evaluate, deploy, and manage deep learning models for practical applications.
Inside this book, you will discover how to:
• Understand the foundations of neural networks, activation functions, backpropagation, and optimization algorithms.
• Build and train deep learning models using TensorFlow and Keras.
• Develop computer vision applications with convolutional neural networks and transfer learning.
• Create natural language processing solutions using transformers and large language models.
• Explore generative AI, diffusion models, and multimodal artificial intelligence systems.
• Build real-world projects for image classification, sentiment analysis, and time series forecasting.
• Deploy models using APIs, MLOps practices, and edge AI technologies.
• Apply explainable AI techniques to improve model transparency and interpretability.
• Learn the fundamentals of reinforcement learning and intelligent agents.
• Understand ethical considerations, responsible AI practices, privacy, security, and future trends in artificial intelligence.
Whether you are beginning your deep learning journey or expanding your existing knowledge, this book provides the theoretical foundation and practical skills needed to develop modern AI solutions.
By the end of this book, you will have the confidence to build intelligent systems, deploy production-ready models, and explore the rapidly evolving landscape of generative artificial intelligence.
Learn. Build. Innovate.
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