BPB is Asia's largest publishers of Computer & IT books. For the last 63 years BPB has been a friend, philosopher and guide for programmers, developers, hardware technicians, IT Professionals who have made things happen in the IT World.
Wydawnictwo BPB Publications - ebooki
Tytuły książek wydawnictwa: BPB Publications
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Come and join hands together to learn Python from scratch. This book will help you understand Python from scratch and help you build a career in the field of programming. Key Features Exciting examples and a solid grasp of the principles of Python. An easy guide for absolute beginners to enjoy coding while learning. Exception handling, OOPs fu-
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step-by-step approach to Python programming with machine learning fundamental and theoretical principles. Key Features Introduces readers to Python programming in a very simple way. Extensive practical demonstration of Python concepts using numerous examples. Implementation of machine learning in Python using hands-on techniques. Description
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A problem-focused guide for tackling industrial machine learning issues with methods and frameworks chosen by experts. Key Features Popular techniques for problem formulation, data collection, and data cleaning in machine learning. Comprehensive and useful machine learning tools such as MLFlow, Streamlit, and many more. Covers numerous machine
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Unlock the Potential of Data Science and Machine Learning to Your Business and Organization Key Features Includes today's most popular applications powered by data science and machine learning technology. A solid primer on the entire data science lifecycle, detailed with examples. An integrated approach to demonstrating the use of Image Proces
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Bring elasticity and innovation to Machine Learning and AI operations Key Features Coverage includes a wide range of AWS AI and ML services to help you speedily get fully operational with ML. Packed with real-world examples, practical guides, and expert data science methods for improving AI/ML education on AWS. Includes ready-made, purpose-bui
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Accelerate the delivery of software, data, and machine learning Key Features Each chapter harmonizes the DevOps, Data Engineering, and Optimized Machine Learning cultures. Equips readers with AGILE skills to continuously re-prioritize production backlogs. Containerization, Docker, Kubernetes, DataOps, and MLOps are all rolled together. Descr
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An insightful journey to MLOps, DevOps, and Machine Learning in the real environment. Key Features Extensive knowledge and concept explanation of Kubernetes components with examples. An all-in-one knowledge guide to train and deploy ML pipelines using Docker and Kubernetes. Includes numerous MLOps projects with access to proven frameworks and
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Description Data engineering is the art of building and managing data pipelines that enable efficient data flow for AI/ML projects. This book serves as a comprehensive guide to data engineering for AI/ML systems, equipping you with the knowledge and skills to create robust and scalable data infrastructure. This book covers everything from foundati
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Build machine learning models and train them to make Android applications much smarter. Key Features Learn by doing, training, and evaluating your own machine learning models. Includes pre-trained TensorFlow models for image processing. Explains practical use cases of artificial intelligence in Android. Description This book features techniqu
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Build production-ready machine learning and NLP systems using functional programming, development platforms, and cloud deployment. Key Features In-depth explanation and code samples highlighting the features of the Julia language. Extensive coverage of the Julia development ecosystem, package management, DevOps environment integration, and perf
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Build AI applications using Python to intelligently interact with the world around you. Key Features Covers the practical aspects of Machine Learning and Deep Learning concepts with the help of this example-rich guide to Python. Includes graphical illustrations of Natural Language Processing and its implementation in NLTK. Covers deep learning
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Work with TensorFlow and Keras for real performance of deep learning Key Features Combines theory and implementation with in-detail use-cases. Coverage on both, TensorFlow 1.x and 2.x with elaborated concepts. Exposure to Distributed Training, GANs and Reinforcement Learning. Description Mastering TensorFlow 2.x is a must to read and practic
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For programmers who need to use Python for network-related activities and apps Key Features Comprehensive coverage of Python 3's improved SSL support. Create an asynchronous I/O loop on your own. A look at the "asyncio" framework, which is included with Python 3.4. Description This book includes revisions for Python 3 as well as all of the
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Introducing Practical Smart Agents Development using Python, PyTorch, and TensorFlow Key Features Exposure to well-known RL techniques, including Monte-Carlo, Deep Q-Learning, Policy Gradient, and Actor-Critical. Hands-on experience with TensorFlow and PyTorch on Reinforcement Learning projects. Everything is concise, up-to-date, and visually
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Explore the cosmic secrets of Distributed Processing for Deep Learning applications. Key Features In-depth practical demonstration of ML/DL concepts using Distributed Framework. Covers graphical illustrations and visual explanations for ML/DL pipelines. Includes live codebase for each of NLP, computer vision and machine learning applications.
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Mathematical Codebook to Navigate Through the Fast-changing AI Landscape Key Features Access to industry-recognized AI methodology and deep learning mathematics with simple-to-understand examples. Encompasses MDP Modeling, the Bellman Equation, Auto-regressive Models, BERT, and Transformers. Detailed, line-by-line diagrams of algorithms, and t
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A complete guide that will help you get familiar with Machine Learning models, algorithms, and optimization techniques Key Features Understand the core concepts and algorithms of Machine Learning. Get started with your Machine Learning career with this easy-to-understand guide. Discover different Machine Learning use cases across different do
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Make use of the most advanced machine learning techniques to perform NLP and feature extraction Key Features Learn about pre-trained models, deep learning, and transfer learning for NLP applications. All-in-one knowledge guide for feature engineering, NLP models, and pre-processing techniques. Includes use cases, enterprise deployments, and a
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Develop AI based real-world Applications Key Features Provides a practical understanding of AI, including its concepts, tools and techniques. Includes step-by-by-step instructions for implementing machine learning and deep learning algorithms and features. Complex datasets and examples are used to expose mathematical illustrative and pseudo-co
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Primer into the multidisciplinary world of Data Science Key Features Explore and use the key concepts of Statistics required to solve data science problems Use Docker, Jenkins, and Git for Continuous Development and Continuous Integration of your web app Learn how to build Data Science solutions with GCP and AWS Description The bo
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Conceptualizing deep learning in computer vision applications using PyTorch and Python libraries. Key Features Covers a variety of computer vision projects, including face recognition and object recognition such as Yolo, Faster R-CNN. Includes graphical representations and illustrations of neural networks and teaches how to program them. Inclu
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A Cookbook that will help you implement Machine Learning algorithms and techniques by building real-world projects Key Features Learn how to handle an entire Machine Learning Pipeline supported with adequate mathematics. Create Predictive Models and choose the right model for various types of Datasets. Learn the art of tuning a mod
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Solve business problems with data-driven techniques and easy-to-follow Python examples Key Features Essential coverage on statistics and data science techniques. Exposure to Jupyter, PyCharm, and use of GitHub. Real use-cases, best practices, and smart techniques on the use of data science for data applications. Description This book
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An easy-to-understand guide to learn practical Machine Learning techniques with Mathematical foundations Key Features A balanced combination of underlying mathematical theories & practical examples with Python code Coverage of latest topics like multi-label classification, Text Mining, Doc2Vec, Word2Vec, XMeans clustering, unsupervised
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A practical guide that will help you understand the Statistical Foundations of any Machine Learning Problem. Key Features Develop a Conceptual and Mathematical understanding of Statistics Get an overview of Statistical Applications in Python Learn how to perform Hypothesis testing in Statistics Understand why Statistics is important in M
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Doors are never locked for smart software and smart devices that are trained by smart people Key Features A book for everyone interested to know more about WSN, AI, and IoT Discover various Open source tools & techniques for research and development in these felids An easy-to-understand guide that will help you get familiar with the upcomi
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A power-packed guide with solutions to crack a Big data Hadoop Interview Key Features Get familiar with Big data concepts Understand the working of Hadoop and its ecosystem. Understand the working of HBase, Pig, Hive, Flume, Sqoop and Spark Understand the capabilities of Big data including Hadoop and HDFS Up and running with
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Get answers to frequently asked questions on Data Science and Machine Learning using R Key Features Understand the capabilities of the R programming language Most of the machine learning algorithms and their R implementation covered in depth Answers on conceptual data science concepts are also covered Description This book
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Understand the essentials of Machine Learning and its impact in financial sector Key Features Explore the spectrum of machine learning and its usage. Understand the NLP and Computer Vision and their use cases. Understand the Neural Network, CNN, RNN and their applications. Understand the Reinforcement Learning and their applications.
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A pragmatic guide that will teach you to implement Agile, SCRUM and Kanban in your organization. Key Features Expert-guided techniques for successful Agile transformation in your organization. Solution-focused responses on interview questions of Agile SCRUM, XP, DSDM, KANBAN and SCRUMBAN. Reference guide to prepare for leading PMI-ACP
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Learn how to work towards making the most out of a career in emerging tech Key Features Understand the core concepts related to careers in emerging tech. Learn innovative, exclusive, and exciting ways to design a successful career in ET. Reduce your learning curve by examining the career trajectories of eminent ET professionals.
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A comprehensive guide to Deep Learning for Beginners Key Features Learn how to design your own neural network efficiently. Learn how to build and train Recurrent Neural Networks (RNNs). Understand how encoding and decoding work in Deep Neural Networks. Description Deep Learning has become increasingly important due to the growing need to pro
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Learn how to deploy complex machine learning models on single board computers, mobile phones, and microcontrollers Key Features Gain a comprehensive understanding of TinyML's core concepts. Learn how to design your own TinyML applications from the ground up. Explore cutting-edge models, hardware, and software platforms for developing TinyML.
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Understand how to leverage Hyperautomation and Generative AI to accelerate Business Transformation Key Features Explores a wide range of use cases and examples that demonstrate the diverse applications of Hyperautomation across industries, sectors, and specific departments. Familiarizes you with popular tools and platforms like UiPath, Automati
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Learn how to build an end-to-end data to AI solution on Google Cloud using Vertex AI Key Features Harness the power of AutoML capabilities to build machine learning models. Learn how to train custom machine learning models on the Google Cloud Platform. Accelerate your career in data analytics by leveraging the capabilities of GCP. Descriptio
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Learn how to build a complete machine learning pipeline by mastering feature extraction, feature selection, and algorithm training Key Features Develop a solid understanding of foundational principles in machine learning. Master regression and classification methods for accurate data prediction and categorization in machine learning. Dive into
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Deploy, manage, and scale Machine Learning models with MLOps effortlessly Key Features Explore several ways to build and deploy ML models in production using an automated CI/CD pipeline. Develop and convert ML apps into Android and Windows apps. Learn how to implement ML model deployment on popular cloud platforms, including Azure, GCP, and AW
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A practical guide that will help you transform your data into actionable insights with Azure Synapse Analytics Key Features Explore the different features in the Azure Synapse Analytics workspace. Learn how to integrate Power BI and Data Governance capabilities with Azure Synapse Analytics. Accelerate your analytics journey with the no-code/lo
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Description In today's data-driven world, the ability to extract meaningful insights from vast datasets is crucial for success in various fields. This ultimate book for mastering open-source libraries of data science in Python equips you with the essential tools and techniques to navigate the ever-evolving field of data analysis and visualization.
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Analyze, Architect, and Innovate with Databricks Lakehouse Key Features Create a Lakehouse using Databricks, including ingestion from source to Bronze. Refinement of Bronze items to business-ready Silver items using incremental methods. Construct Gold items to service the needs of various business requirements. Description The Databricks Lake
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Harness the power of MLOps for managing real time machine learning project cycle Key Features Comprehensive coverage of MLOps concepts, architecture, tools and techniques. Practical focus on building end-to-end ML Systems for Continual Learning with MLOps. Actionable insights on CI/CD, monitoring, continual model training and automated retrain
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Our book explains learning algorithms related to real-world problems, with implementations in languages like R, Python, etc. Key Features Basic understanding of machine learning algorithms via MATLAB, R, and Python. Inclusion of examples related to real-world problems, case studies, and questions related to futuristic technologies. Adding futu
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Architecting AI: Design patterns for building deep learning products Key Features Master foundational concepts in design patterns of deep learning. Benefit from practical insights shared by an industry professional. Learn to build data products using deep learning. Description Design Patterns of Deep Learning with TensorFlow is your comprehen
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Description Fun with Data Analysis and BI teaches you how to turn raw data into actionable insights using business intelligence tools. It equips you with essential skills to make data-driven decisions and effectively communicate findings. This book is designed to guide you through learning SQL from the ground up. Starting with installation and env
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Description "High-Performance Algorithmic Trading using AI" is a comprehensive guide designed to empower both beginners and experienced professionals in the finance industry. This book equips you with the knowledge and tools to build sophisticated, high-performance trading systems. It starts with basics like data preprocessing, feature engineering,
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Unleash the hidden potential of Python to emerge as a change maker of contemporary industry Key Features Explore Python commands for RPA, workflows and hyperautomation. Concise chapters with lucid examples and elaborate codes that make learning interesting. Practical industry use case at the end of every chapter to highlight its real world app
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Turn raw data into meaningful solutions Key Features Complete guide to master data science basics. Practical and hands-on examples in ML, deep learning, and NLP. Drive innovation and improve decision making through the power of data. Description Learn Data Science from Scratch equips you with the essential tools and techniques, from Python li
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Do not just talk AI, build it: Your guide to LLM application development Key Features Explore NLP basics and LLM fundamentals, including essentials, challenges, and model types. Learn data handling and pre-processing techniques for efficient data management. Understand neural networks overview, including NN basics, RNNs, CNNs, and transformers
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This book intends to provide a collection of various MCQs on data science Key Features Comprehensive coverage of data science concepts and features. Multiple-choice questions to test and assess knowledge effectively. Over 5000 multiple-choice questions for practice. Description This book is a comprehensive manual created to assess and improve
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This book is intended to provide a collection of various MCQs of the Python programming language Key Features Comprehensive coverage of Python concepts and features. Over 5000 multiple choice questions to test and assess the readers knowledge effectively. Description This Python Question Bank comprises multiple-choice questions (MCQs) for empl
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Empowering AI innovations: The fusion of microservices and ML Key Features Microservices and ML fundamentals, advancements, and practical applications in various industries. Simplify complex ML development with distributed and scalable microservices architectures. Discover real-world scenarios illustrating the fusion of microservices and ML, s
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Build high-impact ML/AI solutions by optimizing each step Key Features Build and fine-tune models for maximum performance. Practical tips to make your own state-of-the-art AI/ML models. ML/AI problem solving tips with multiple case studies to tackle real-world challenges. Description This book approaches data science solution building using a
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Explore the world of Artificial Intelligence with a deep understanding of Machine Learning concepts and algorithms Key Features A detailed study of mathematical concepts, Machine Learning concepts, and techniques. Discusses methods for evaluating model performances and interpreting results. Explores all types of Machine Learning (supervised, u
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