Видавець: 8
Indra den Bakker
Deep Learning is revolutionizing a wide range of industries. For many applications, deep learning has proven to outperform humans by making faster and more accurate predictions. This book provides a top-down and bottom-up approach to demonstrate deep learning solutions to real-world problems in different areas. These applications include Computer Vision, Natural Language Processing, Time Series, and Robotics. The Python Deep Learning Cookbook presents technical solutions to the issues presented, along with a detailed explanation of the solutions. Furthermore, a discussion on corresponding pros and cons of implementing the proposed solution using one of the popular frameworks like TensorFlow, PyTorch, Keras and CNTK is provided. The book includes recipes that are related to the basic concepts of neural networks. All techniques s, as well as classical networks topologies. The main purpose of this book is to provide Python programmers a detailed list of recipes to apply deep learning to common and not-so-common scenarios.
Ivan Vasilev, Daniel Slater, Gianmario Spacagna, Peter...
With the surge in artificial intelligence in applications catering to both business and consumer needs, deep learning is more important than ever for meeting current and future market demands. With this book, you’ll explore deep learning, and learn how to put machine learning to use in your projects.This second edition of Python Deep Learning will get you up to speed with deep learning, deep neural networks, and how to train them with high-performance algorithms and popular Python frameworks. You’ll uncover different neural network architectures, such as convolutional networks, recurrent neural networks, long short-term memory (LSTM) networks, and capsule networks. You’ll also learn how to solve problems in the fields of computer vision, natural language processing (NLP), and speech recognition. You'll study generative model approaches such as variational autoencoders and Generative Adversarial Networks (GANs) to generate images. As you delve into newly evolved areas of reinforcement learning, you’ll gain an understanding of state-of-the-art algorithms that are the main components behind popular games Go, Atari, and Dota.By the end of the book, you will be well-versed with the theory of deep learning along with its real-world applications.
Valentino Zocca, Gianmario Spacagna, Daniel Slater, Peter...
With an increasing interest in AI around the world, deep learning has attracted a great deal of public attention. Every day, deep learning algorithms are used broadly across different industries.The book will give you all the practical information available on the subject, including the best practices, using real-world use cases. You will learn to recognize and extract information to increase predictive accuracy and optimize results.Starting with a quick recap of important machine learning concepts, the book will delve straight into deep learning principles using Sci-kit learn. Moving ahead, you will learn to use the latest open source libraries such as Theano, Keras, Google's TensorFlow, and H20. Use this guide to uncover the difficulties of pattern recognition, scaling data with greater accuracy and discussing deep learning algorithms and techniques.Whether you want to dive deeper into Deep Learning, or want to investigate how to get more out of this powerful technology, you’ll find everything inside.
Matthew Lamons, Rahul Kumar, Abhishek Nagaraja
Deep learning has been gradually revolutionizing every field of artificial intelligence, making application development easier.Python Deep Learning Projects imparts all the knowledge needed to implement complex deep learning projects in the field of computational linguistics and computer vision. Each of these projects is unique, helping you progressively master the subject. You’ll learn how to implement a text classifier system using a recurrent neural network (RNN) model and optimize it to understand the shortcomings you might experience while implementing a simple deep learning system.Similarly, you’ll discover how to develop various projects, including word vector representation, open domain question answering, and building chatbots using seq-to-seq models and language modeling. In addition to this, you’ll cover advanced concepts, such as regularization, gradient clipping, gradient normalization, and bidirectional RNNs, through a series of engaging projects.By the end of this book, you will have gained knowledge to develop your own deep learning systems in a straightforward way and in an efficient way
Ivan Vasilev, Valentino Zocca
The field of deep learning has developed rapidly recently and today covers a broad range of applications. This makes it challenging to navigate and hard to understand without solid foundations. This book will guide you from the basics of neural networks to the state-of-the-art large language models in use today.The first part of the book introduces the main machine learning concepts and paradigms. It covers the mathematical foundations, the structure, and the training algorithms of neural networks and dives into the essence of deep learning.The second part of the book introduces convolutional networks for computer vision. We’ll learn how to solve image classification, object detection, instance segmentation, and image generation tasks.The third part focuses on the attention mechanism and transformers – the core network architecture of large language models. We’ll discuss new types of advanced tasks they can solve, such as chatbots and text-to-image generation.By the end of this book, you’ll have a thorough understanding of the inner workings of deep neural networks. You'll have the ability to develop new models and adapt existing ones to solve your tasks. You’ll also have sufficient understanding to continue your research and stay up to date with the latest advancements in the field.
Python: Deeper Insights into Machine Learning. Deeper Insights into Machine Learning
John Hearty, Sebastian Raschka, David Julian
Machine learning and predictive analytics are becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. It is one of the fastest growing trends in modern computing, and everyone wants to get into the field of machine learning. In order to obtain sufficient recognition in this field, one must be able to understand and design a machine learning system that serves the needs of a project. The idea is to prepare a learning path that will help you to tackle the real-world complexities of modern machine learning with innovative and cutting-edge techniques. Also, it will give you a solid foundation in the machine learning design process, and enable you to build customized machine learning models to solve unique problems.The course begins with getting your Python fundamentals nailed down. It focuses on answering the right questions that cove a wide range of powerful Python libraries, including scikit-learn Theano and Keras.After getting familiar with Python core concepts, it’s time to dive into the field of data science. You will further gain a solid foundation on the machine learning design and also learn to customize models for solving problems.At a later stage, you will get a grip on more advanced techniques and acquire a broad set of powerful skills in the area of feature selection and feature engineering.
Python Digital Forensics Cookbook. Effective Python recipes for digital investigations
Chapin Bryce, Preston Miller
Technology plays an increasingly large role in our daily lives and shows no sign of stopping. Now, more than ever, it is paramount that an investigator develops programming expertise to deal with increasingly large datasets. By leveraging the Python recipes explored throughout this book, we make the complex simple, quickly extracting relevant information from large datasets. You will explore, develop, and deploy Python code and libraries to provide meaningful results that can be immediately applied to your investigations. Throughout the Python Digital Forensics Cookbook, recipes include topics such as working with forensic evidence containers, parsing mobile and desktop operating system artifacts, extracting embedded metadatafrom documents and executables, and identifying indicators of compromise. Youwill also learn to integrate scripts with Application Program Interfaces (APIs) suchas VirusTotal and PassiveTotal, and tools such as Axiom, Cellebrite, and EnCase. By the end of the book, you will have a sound understanding of Python and how you can use it to process artifacts in your investigations.
Python dla administratorów. Kurs video. Od podstaw do automatyzacji pracy w świecie DevOps
Piotr Kośka
Obierz kurs na... programowanie i administrowanie w języku Python Jeśli zapytać aktywnych specjalistów branży IT o najpopularniejszy obecnie język programowania, większość z nich odpowie bez wahania: Python. Kto zatem rozważa rozpoczęcie kariery jako specjalista DevOps albo jako administrator systemów, zdecydowanie powinien zacząć naukę od opanowania tego języka, ponieważ to w nim przede wszystkim będą operować koledzy po fachu. Nawet jeśli nie chcesz być programistą, ale na przykład myślisz o tym, by usprawnić sobie pracę dzięki wprowadzeniu do niej elementów automatyzacji w systemach Linux lub Windows, znajomość pewnych trików i umiejętność pisania skryptów w Pythonie bardzo ułatwi Ci życie. Także jeżeli chcesz jedynie opanować jakiś język programowania, by korzystać z niego okazjonalnie, rekomendujemy Pythona. Pozwoli Ci on na pisanie testów: jednostkowych, integracyjnych i funkcjonalnych dla aplikacji. Język ten jest powszechnie używany do monitorowania infrastruktury, jak również do analizowania logów i wizualizacji związanych z nimi danych. Znajomość Pythona po prostu Ci się przyda. Prędzej czy później. Wraz z kursem video Python dla administratorów opanujesz podstawy języka Python. Zastanawiasz się pewnie, czy to trudne. Czy jest trudniejsze, a może łatwiejsze niż w wypadku innych języków programowania? Dobre pytanie, a odpowiedź jeszcze lepsza, ponieważ Python jest jednym z najbardziej przystępnych języków programowania. Łatwy w nauce, ma prostą, intuicyjną składnię, czyli sposób zapisu poleceń rozumianych przez komputer za pomocą danego języka programowania. Jego składnia przypomina składnię ludzkiej mowy. Słowa kluczowe są więc zrozumiałe dla każdego początkującego, a jednocześnie bardzo bliskie tym występującym w innych językach programowania - dlatego ewentualna "przesiadka" na inny język będzie prostsza. Co Cię czeka podczas naszego profesjonalnego szkolenia video Python dla administratorów? Z kursu Python dla administratorów dowiesz się między innymi: Jak zainstalować Pythona w systemach Linux i Windows Czym się charakteryzują różne typy danych, w tym int, float, bool i none Czym są lista i tuple Na czym bazują słowniki Jak działają instrukcje warunkowe (if, else, elif), a jak pętle (while, for) Do czego używane są operatory logiczne Kiedy stosować input i output Jakie są funkcje w języku Python Jak tworzyć skrypty, które automatyzują codzienną pracę Jak pisać testy w Pythonie Co więcej, w ramach proponowanego szkolenia: Poznasz sposoby korzystania z bibliotek zewnętrznych Python dla administratorów. Kurs video. Od podstaw do automatyzacji pracy w świecie DevOps wyposaży Cię w podstawowe umiejętności potrzebne do pracy z systemami Linux i Windows na poziomie terminala. Zdobędziesz także bazowe umiejętności, jeśli chodzi o programowanie w dowolnym języku skryptowym, i poznasz dobre nawyki w pracy specjalisty DevOps. "Hello, World!", czyli jak prosty jest Python Napiszmy najprostszy program, którego celem jest wyświetlenie komunikatu "Hello, World!" (Witaj, świecie!). W Pythonie kod źródłowy będzie wyglądał następująco: print("Hello, World!") Dla porównania sprawdźmy, jak wyglądałby w Javie: public class HelloWorld { public static void main(String[] args) { System.out.println("Hello, World"); } } Różnica jest widoczna na pierwszy rzut oka. Jeśli chcesz się nauczyć prostego i efektywnego języka, jakim jest Python - zapraszamy Cię na kurs! Zainteresować cię mogą także kursy video ASP.NET dostępne w naszej ofercie.