From the Back Cover
Discover the practical aspects of implementing deep-learning solutions using the rich Python ecosystem. This book bridges the gap between the academic state-of-the-art and the industry state-of-the-practice by introducing you to deep learning frameworks such as Keras, Theano, and Caffe. The practicalities of these frameworks is often acquired by practitioners by reading source code, manuals, and posting questions on community forums, which tends to be a slow and a painful process.Deep Learning with Pythonallows you to ramp up to such practical know-how in a short period of time and focus more on the domain, models, and algorithms.This book briefly covers the mathematical prerequisites and fundamentals of deep learning, making this book a good starting point for software developers who want to get started in deep learning. A brief survey of deep learning architectures is also included.Deep Learning with Pythonalso introduces you to key concepts of automatic differentiation and GPU computation which, while not central to deep learning, are critical when it comes to conducting large scale experiments.You will:Leverage deep learning frameworks in Python namely, Keras, Theano, and CaffeGain the fundamentals of deep learning with mathematical prerequisitesDiscover the practical considerations of large scale experimentsTake deep learning models to production
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About the Author
Nikhil S. Ketkar currently leads the Machine Learning Platform team at Flipkart, India’s largest e-commerce company. He received his Ph.D. from Washington State University. Following that he conducted postdoctoral research at University of North Carolina at Charlotte, which was followed by a brief stint in high frequency trading at Transmaket in Chicago. More recently he led the data mining team in Guavus, a startup doing big data analytics in the telecom domain and Indix, a startup doing data science in the e-commerce domain. His research interests include machine learning and graph theory.
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Discover the practical aspects of implementing deep-learning solutions using the rich Python ecosystem. This book bridges the gap between the academic state-of-the-art and the industry state-of-the-practice by introducing you to deep learning frameworks such as Keras, Theano, and Caffe. The practicalities of these frameworks is often acquired by practitioners by reading source code, manuals, and posting questions on community forums, which tends to be a slow and a painful process. Deep Learning with Python allows you to ramp up to such practical know-how in a short period of time and focus more on the domain, models, and algorithms.
This book briefly covers the mathematical prerequisites and fundamentals of deep learning, making this book a good starting point for software developers who want to get started in deep learning. A brief survey of deep learning architectures is also included.
Deep Learning with Python also introduces you to key concepts of automatic differentiation and GPU computation which, while not central to deep learning, are critical when it comes to conducting large scale experiments.
What You Will Learn
Leverage deep learning frameworks in Python namely, Keras, Theano, and CaffeGain the fundamentals of deep learning with mathematical prerequisitesDiscover the practical considerations of large scale experimentsTake deep learning models to production
Who This Book Is ForSoftware developers who want to try out deep learning as a practical solution to a particular problem.Software developers in a data science team who want to take deep learning models developed by data scientists to production.
發表於2024-11-14
Deep Learning with Python 2024 pdf epub mobi 電子書 下載
圖書標籤: 深度學習 Python 機器學習 人工智能 AI
利用openCV+Keras破解驗證碼,不僅僅是圖片識彆,更是深度學習和計算機視覺技術的良好開端。簡單來說,用WordPress獲取驗證碼後,將驗證碼圖像分割成獨立字符,調用神經網絡對獨立的字符塊進行預測,將多個預測結果排列以作為該 驗證碼的返迴結果。
評分https://github.com/greatabel/MachineLearning/tree/master/05Deep%20Learning%20with%20Python-%20A%20Hands-on%20Introduction
評分https://github.com/greatabel/MachineLearning/tree/master/05Deep%20Learning%20with%20Python-%20A%20Hands-on%20Introduction
評分利用openCV+Keras破解驗證碼,不僅僅是圖片識彆,更是深度學習和計算機視覺技術的良好開端。簡單來說,用WordPress獲取驗證碼後,將驗證碼圖像分割成獨立字符,調用神經網絡對獨立的字符塊進行預測,將多個預測結果排列以作為該 驗證碼的返迴結果。
評分利用openCV+Keras破解驗證碼,不僅僅是圖片識彆,更是深度學習和計算機視覺技術的良好開端。簡單來說,用WordPress獲取驗證碼後,將驗證碼圖像分割成獨立字符,調用神經網絡對獨立的字符塊進行預測,將多個預測結果排列以作為該 驗證碼的返迴結果。
Deep Learning with Python 2024 pdf epub mobi 電子書 下載