Hands-On Artificial Intelligence for Banking. A practical guide to building intelligent financial applications using machine learning techniques

Jeffrey Ng, Subhash Shah

Remodeling your outlook on banking begins with keeping up to date with the latest and most effective approaches, such as artificial intelligence (AI). Hands-On Artificial Intelligence for Banking is a practical guide that will help you advance in your career in the banking domain. The book will demonstrate AI implementation to make your banking services smoother, more cost-efficient, and accessible to clients, focusing on both the client- and server-side uses of AI.You’ll begin by understanding the importance of artificial intelligence, while also gaining insights into the recent AI revolution in the banking industry. Next, you’ll get hands-on machine learning experience, exploring how to use time series analysis and reinforcement learning to automate client procurements and banking and finance decisions. After this, you’ll progress to learning about mechanizing capital market decisions, using automated portfolio management systems and predicting the future of investment banking. In addition to this, you’ll explore concepts such as building personal wealth advisors and mass customization of client lifetime wealth. Finally, you’ll get to grips with some real-world AI considerations in the field of banking. By the end of this book, you’ll be equipped with the skills you need to navigate the finance domain by leveraging the power of AI.

Hands-On Business Intelligence with DAX. Discover the intricacies of this powerful query language to gain valuable insights from your data

Ian Horne

Data Analysis Expressions (DAX) is known for its ability to increase efficiency by extracting new information from data that is already present in your model. With this book, you’ll learn to use DAX’s functionality and flexibility in the BI and data analytics domains.You’ll start by learning the basics of DAX, along with understanding the importance of good data models, and how to write efficient DAX formulas by using variables and formatting styles. You’ll then explore how DAX queries work with the help of examples. The book will guide you through optimizing the BI workflow by writing powerful DAX queries. Next, you’ll learn to manipulate and load data of varying complexity within Microsoft products such as Power BI, SQL Server, and Excel Power Pivot. You’ll then discover how to build and extend your data models to gain additional insights, before covering progressive DAX syntax and functions to understand complex relationships in DAX. Later, you’ll focus on important DAX functions, specifically those related to tables, date and time, filtering, and statistics. Finally, you’ll delve into advanced topics such as how the formula and storage engines work to optimize queries.By the end of this book, you’ll have gained hands-on experience in employing DAX to enhance your data models by extracting new information and gaining deeper insights.

Hands-On Computer Vision with Detectron2. Develop object detection and segmentation models with a code and visualization approach

Van Vung Pham, Tommy Dang

Computer vision is a crucial component of many modern businesses, including automobiles, robotics, and manufacturing, and its market is growing rapidly. This book helps you explore Detectron2, Facebook's next-gen library providing cutting-edge detection and segmentation algorithms. It’s used in research and practical projects at Facebook to support computer vision tasks, and its models can be exported to TorchScript or ONNX for deployment.The book provides you with step-by-step guidance on using existing models in Detectron2 for computer vision tasks (object detection, instance segmentation, key-point detection, semantic detection, and panoptic segmentation). You’ll get to grips with the theories and visualizations of Detectron2’s architecture and learn how each module in Detectron2 works. As you advance, you’ll build your practical skills by working on two real-life projects (preparing data, training models, fine-tuning models, and deployments) for object detection and instance segmentation tasks using Detectron2. Finally, you’ll deploy Detectron2 models into production and develop Detectron2 applications for mobile devices.By the end of this deep learning book, you’ll have gained sound theoretical knowledge and useful hands-on skills to help you solve advanced computer vision tasks using Detectron2.

Hands-On Graph Neural Networks Using Python. Practical techniques and architectures for building powerful graph and deep learning apps with PyTorch

Maxime Labonne

Graph neural networks are a highly effective tool for analyzing data that can be represented as a graph, such as social networks, chemical compounds, or transportation networks. The past few years have seen an explosion in the use of graph neural networks, with their application ranging from natural language processing and computer vision to recommendation systems and drug discovery.Hands-On Graph Neural Networks Using Python begins with the fundamentals of graph theory and shows you how to create graph datasets from tabular data. As you advance, you’ll explore major graph neural network architectures and learn essential concepts such as graph convolution, self-attention, link prediction, and heterogeneous graphs. Finally, the book proposes applications to solve real-life problems, enabling you to build a professional portfolio. The code is readily available online and can be easily adapted to other datasets and apps.By the end of this book, you’ll have learned to create graph datasets, implement graph neural networks using Python and PyTorch Geometric, and apply them to solve real-world problems, along with building and training graph neural network models for node and graph classification, link prediction, and much more.

Hands-On Music Generation with Magenta. Explore the role of deep learning in music generation and assisted music composition

Alexandre DuBreuil

The importance of machine learning (ML) in art is growing at a rapid pace due to recent advancements in the field, and Magenta is at the forefront of this innovation. With this book, you’ll follow a hands-on approach to using ML models for music generation, learning how to integrate them into an existing music production workflow. Complete with practical examples and explanations of the theoretical background required to understand the underlying technologies, this book is the perfect starting point to begin exploring music generation.The book will help you learn how to use the models in Magenta for generating percussion sequences, monophonic and polyphonic melodies in MIDI, and instrument sounds in raw audio. Through practical examples and in-depth explanations, you’ll understand ML models such as RNNs, VAEs, and GANs. Using this knowledge, you’ll create and train your own models for advanced music generation use cases, along with preparing new datasets. Finally, you’ll get to grips with integrating Magenta with other technologies, such as digital audio workstations (DAWs), and using Magenta.js to distribute music generation apps in the browser.By the end of this book, you'll be well-versed with Magenta and have developed the skills you need to use ML models for music generation in your own style.

Hands-On Simulation Modeling with Python. Develop simulation models for improved efficiency and precision in the decision-making process - Second Edition

Giuseppe Ciaburro

Simulation modelling is an exploration method that aims to imitate physical systems in a virtual environment and retrieve useful statistical inferences from it. The ability to analyze the model as it runs sets simulation modelling apart from other methods used in conventional analyses. This book is your comprehensive and hands-on guide to understanding various computational statistical simulations using Python. The book begins by helping you get familiarized with the fundamental concepts of simulation modelling, that’ll enable you to understand the various methods and techniques needed to explore complex topics. Data scientists working with simulation models will be able to put their knowledge to work with this practical guide. As you advance, you’ll dive deep into numerical simulation algorithms, including an overview of relevant applications, with the help of real-world use cases and practical examples. You'll also find out how to use Python to develop simulation models and how to use several Python packages. Finally, you’ll get to grips with various numerical simulation algorithms and concepts, such as Markov Decision Processes, Monte Carlo methods, and bootstrapping techniques.By the end of this book, you'll have learned how to construct and deploy simulation models of your own to overcome real-world challenges.

Hyperledger Cookbook. Over 40 recipes implementing the latest Hyperledger blockchain frameworks and tools

Xun (Brian) Wu, Chuanfeng Zhang, Zhibin (Andrew) Zhang

Hyperledger is an open-source project and creates private blockchain applications for a range of domains. This book will be your desk reference as you explore common and not-so-common challenges faced while building blockchain networks using Hyperledger services.We'll work through all Hyperledger platform modules to understand their services and features and build end-to-end blockchain applications using various frameworks and tools supported by Hyperledger. This book's independent, recipe-based approach (packed with real-world examples) will familiarize you with the blockchain development cycle. From modeling a business network to integrating with various tools, you will cover it all. We'll cover common and not-so-common challenges faced in the blockchain life cycle. Later, we'll delve into how we can interact with the Hyperledger Fabric blockchain, covering all the principles you need to master, such as chaincode, smart contracts, and much more. We'll also address the scalability and security issues currently faced in blockchain development.By the end of this book, you will be able to implement each recipe to plan, design, and create a full-fledged, private, decentralized application to meet organizational needs.

Hyperparameter Tuning with Python. Boost your machine learning model’s performance via hyperparameter tuning

Louis Owen

Hyperparameters are an important element in building useful machine learning models. This book curates numerous hyperparameter tuning methods for Python, one of the most popular coding languages for machine learning. Alongside in-depth explanations of how each method works, you will use a decision map that can help you identify the best tuning method for your requirements.You’ll start with an introduction to hyperparameter tuning and understand why it's important. Next, you'll learn the best methods for hyperparameter tuning for a variety of use cases and specific algorithm types. This book will not only cover the usual grid or random search but also other powerful underdog methods. Individual chapters are also dedicated to the three main groups of hyperparameter tuning methods: exhaustive search, heuristic search, Bayesian optimization, and multi-fidelity optimization. Later, you will learn about top frameworks like Scikit, Hyperopt, Optuna, NNI, and DEAP to implement hyperparameter tuning. Finally, you will cover hyperparameters of popular algorithms and best practices that will help you efficiently tune your hyperparameter.By the end of this book, you will have the skills you need to take full control over your machine learning models and get the best models for the best results.

Implementing Microsoft Dynamics 365 Customer Engagement. Configure, customize, and extend Dynamics 365 CE in order to create effective CRM solutions

Mahender Pal

Microsoft Dynamics 365 for Customer Engagement (CE) is one of the leading customer relationship management (CRM) solutions that help companies to effectively communicate with their customers and allows them to transform their marketing strategies. Complete with detailed explanations of the essential concepts and practical examples, this book will guide you through the entire life cycle of implementing Dynamics 365 CE for your organization or clients, and will help you avoid common pitfalls while increasing efficiency at every stage of the project. Starting with the foundational concepts, the book will gradually introduce you to Microsoft Dynamics 365 features, plans, and products. You’ll learn various implementation strategies and requirement gathering techniques, and then design the application architecture by converting your requirements into technical and functional designs. As you advance, you’ll learn how to configure your CRM system to meet your organizational needs, customize Dynamics 365 CE, and extend its capabilities by writing client-side and server-side code. Finally, you’ll integrate Dynamics 365 CE with other applications and explore its business intelligence capabilities. By the end of this Microsoft Dynamics 365 book, you’ll have gained an in-depth understanding of all the key components necessary for successful Dynamics 365 CE implementation.

Implementing Splunk. A comprehensive guide to help you transform Big Data into valuable business insights with Splunk 6.2

James D. Miller, VINCENT BUMGARNER

Industrial Digital Transformation. Accelerate digital transformation with business optimization, AI, and Industry 4.0

Shyam Varan Nath, Ann Dunkin, Mahesh Chowdhary, Nital Patel

Digital transformation requires the ability to identify opportunities across industries and apply the right technologies and tools to achieve results. This book is divided into two parts with the first covering what digital transformation is and why it is important. The second part focuses on how digital transformation works.After an introduction to digital transformation, you will explore the transformation journey in logical steps and understand how to build business cases and create productivity benefit statements. Next, you’ll delve into advanced topics relating to overcoming various challenges. Later, the book will take you through case studies in both private and public sector organizations. You’ll explore private sector organizations such as industrial and hi-tech manufacturing in detail and get to grips with public sector organizations by learning how transformation can be achieved on a global scale and how the resident experience can be improved. In addition to this, you will understand the role of artificial intelligence, machine learning and deep learning in digital transformation. Finally, you’ll discover how to create a playbook that can ensure success in digital transformation.By the end of this book, you’ll be well-versed with industrial digital transformation and be able to apply your skills in the real world.

Integrate Lua with C++. Seamlessly integrate Lua scripting to enhance application flexibility

Wenhuan Li

C++ is a popular choice in the developer community for building complex and large-scale performant applications and systems. Often a need arises to extend the system at runtime, without recompiling the whole C++ program. Using a scripting language like Lua can help achieve this goal efficiently.Integrate Lua to C++ is a comprehensive guide to integrating Lua to C++ and will enable you to achieve the goal of extending C++ programs at runtime. You’ll learn, in sequence, how to get and compile the Lua library, the Lua programming language, calling Lua code from C++, and calling C++ code from Lua. In each topic, you’ll practice with code examples, and learn the in-depth mechanisms for smooth working. Throughout the book, the latter examples build on the earlier ones while also acting as a standalone. You’ll learn to implement Lua executor and Lua binding generator, which you can use in your projects directly with further customizations.By the end of this book, you’ll have mastered integrating Lua into C++ and using Lua in your C++ project efficiently, gained the skills to extend your applications at runtime, and achieved dynamic and adaptable C++ development.

Intelligent Document Processing with AWS AI/ML. A comprehensive guide to building IDP pipelines with applications across industries

Sonali Sahu

With the volume of data growing exponentially in this digital era, it has become paramount for professionals to process this data in an accelerated and cost-effective manner to get value out of it. Data that organizations receive is usually in raw document format, and being able to process these documents is critical to meeting growing business needs.This book is a comprehensive guide to helping you get to grips with AI/ML fundamentals and their application in document processing use cases. You’ll begin by understanding the challenges faced in legacy document processing and discover how you can build end-to-end document processing pipelines with AWS AI services. As you advance, you'll get hands-on experience with popular Python libraries to process and extract insights from documents. This book starts with the basics, taking you through real industry use cases for document processing to deliver value-based care in the healthcare industry and accelerate loan application processing in the financial industry. Throughout the chapters, you'll find out how to apply your skillset to solve practical problems.By the end of this AWS book, you’ll have mastered the fundamentals of document processing with machine learning through practical implementation.

Inżynieria promptów bez tajemnic. Sztuka kreatywnego generowania tekstów

Gilbert Mizrahi

Pojawienie się dużych modeli językowych, takich jak GPT-4 czy Gemini, okazało się prawdziwym przełomem w wielu branżach. Modele te potrafią generować znakomite teksty i prowadzić zaawansowane konwersacje. Z ich potencjału można czerpać poprzez odpowiednio sformułowane prompty. Aby więc w pełni skorzystać z możliwości modelu do wykonania konkretnego zadania, trzeba opanować sztukę pisania promptów. Na podstawie tej praktycznej książki nauczysz się pisać skuteczne prompty dla dużych modeli językowych. Dowiesz się, w jaki sposób mogą posłużyć do generowania opisów produktów, spersonalizowanych wiadomości e-mail, postów w mediach społecznościowych, a nawet tekstów beletrystycznych i poetyckich. Poznasz także zaawansowane techniki użycia, takie jak integracja dużych modeli językowych z innymi narzędziami i tworzenie chatbotów. Wszystkie opisane tu techniki przetestujesz, eksperymentując i optymalizując swoje rozwiązania. W efekcie zdobędziesz umiejętności, które pozwolą Ci wykonywać codzienne zadania szybciej i lepiej! Dzięki tej książce: poznasz różne typy promptów i ich zastosowania rozwiniesz umiejętności kreatywnego pisania, korzystając ze sztucznej inteligencji zdobędziesz zaawansowane umiejętności tworzenia i wdrażania chatbotów nauczysz się integrować duże modele językowe z innymi narzędziami poznasz zagadnienia etyczne i najlepsze praktyki związane ze sztuczną inteligencją Moc promptów w Twoich rękach ― twórz, inspiruj, zaskakuj!

IoT and Edge Computing for Architects. Implementing edge and IoT systems from sensors to clouds with communication systems, analytics, and security - Second Edition

Perry Lea

Industries are embracing IoT technologies to improve operational expenses, product life, and people's well-being. An architectural guide is needed if you want to traverse the spectrum of technologies needed to build a successful IoT system, whether that's a single device or millions of IoT devices. IoT and Edge Computing for Architects, Second Edition encompasses the entire spectrum of IoT solutions, from IoT sensors to the cloud. It examines modern sensor systems, focusing on their power and functionality. It also looks at communication theory, paying close attention to near-range PAN, including the new Bluetooth® 5.0 specification and mesh networks. Then, the book explores IP-based communication in LAN and WAN, including 802.11ah, 5G LTE cellular, Sigfox, and LoRaWAN. It also explains edge computing, routing and gateways, and their role in fog computing, as well as the messaging protocols of MQTT 5.0 and CoAP.With the data now in internet form, you'll get an understanding of cloud and fog architectures, including the OpenFog standards. The book wraps up the analytics portion with the application of statistical analysis, complex event processing, and deep learning models. The book then concludes by providing a holistic view of IoT security, cryptography, and shell security in addition to software-defined perimeters and blockchains.

Jak zarabiać przez Internet z AI

Włodzimierz Iwanowski

Freelancing wspomagany mocą sztucznej inteligencji? To działa! Wchodzimy w erę dynamicznych zmian związanych ze sztuczną inteligencją. Spodziewaliśmy się tego i już to widzimy ― AI rewolucjonizuje nasze życie, zmienia codzienne funkcjonowanie, ale również (a może przede wszystkim) zaczyna wpływać na sposób zarobkowania. Ten, kto szybciej nauczy się efektywnie korzystać z jej narzędzi, tego czeka sukces finansowy. Dotyczy to także osób z branży kreatywnej, pracujących na zlecenie. Ta książka wprowadzi Cię do świata najpopularniejszych platform freelancerskich, za których pośrednictwem możesz oferować swoje usługi, takich jak Fiverr, Upwork czy Useme. Autor podpowie Ci, jak dzięki narzędziom sztucznej inteligencji wykonać swoją pracę szybciej i efektywniej, niezależnie od tego, czy przygotowujesz audiobook, nagrywasz podcast, komponujesz muzykę, budujesz grę, piszesz dowolny tekst, czy... tworzysz wirtualnego influencera. W poradniku znajdziesz również praktyczne porady, jak zarządzać ryzykiem, jak reagować na negatywne opinie i jak unikać najczęstszych błędów finansowych. Książka w mediach: Books4Busines Bookstagram Bielicka Bookstagram

Java Deep Learning Essentials. Unlocking the next generation of predictive power

Yusuke Sugomori

AI and Deep Learning are transforming the way we understand software, making computers more intelligent than we could even imagine just a decade ago. Deep Learning algorithms are being used across a broad range of industries – as the fundamental driver of AI, being able to tackle Deep Learning is going to a vital and valuable skill not only within the tech world but also for the wider global economy that depends upon knowledge and insight for growth and success. It’s something that’s moving beyond the realm of data science – if you’re a Java developer, this book gives you a great opportunity to expand your skillset.Starting with an introduction to basic machine learning algorithms, to give you a solid foundation, Deep Learning with Java takes you further into this vital world of stunning predictive insights and remarkable machine intelligence. Once you’ve got to grips with the fundamental mathematical principles, you’ll start exploring neural networks and identify how to tackle challenges in large networks using advanced algorithms. You will learn how to use the DL4J library and apply Deep Learning to a range of real-world use cases. Featuring further guidance and insights to help you solve challenging problems in image processing, speech recognition, language modeling, this book will make you rethink what you can do with Java, showing you how to use it for truly cutting-edge predictive insights. As a bonus, you’ll also be able to get to grips with Theano and Caffe, two of the most important tools in Deep Learning today.By the end of the book, you’ll be ready to tackle Deep Learning with Java. Wherever you’ve come from – whether you’re a data scientist or Java developer – you will become a part of the Deep Learning revolution!

Języki i paradygmaty programowania. Teoria i praktyka

Feliks Kurp

Czym w rzeczywistości jest programowanie? I jak zacząć programować? Oprogramowanie jest dziś praktycznie wszędzie, a programiści od dawna należą do najbardziej poszukiwanych specjalistów. Na podstawie napisanego przez nich kodu funkcjonują już nie tylko komputery i smartfony. Oprogramowanie steruje sprzętami domowymi, telewizorem czy lodówką. W ramach tak zwanego internetu rzeczy wiele urządzeń technicznych komunikuje się między sobą bez udziału człowieka. Gwałtownie rozwija się sztuczna inteligencja, wymagająca specjalistycznego oprogramowania. Nie dziwi więc, że jego rozwój ciągle przyspiesza. W obliczu tych faktów odpowiedź na pytanie, jakiego języka programowania warto się nauczyć, jest trudna. Nawet dla osoby, która wie, w jaki sposób zamierza w przyszłości korzystać ze swoich informatycznych umiejętności. Autor książki proponuje nieco inne podejście do nauki programowania. Zachęca do zapoznania się z podstawowymi własnościami i możliwymi zastosowaniami kilku odległych od siebie, ale niezwykle ważnych aktualnie języków programowania, takich jak Python, Java SE, JavaScript i Prolog. W trakcie ich poznawania czytelnicy będą mieli okazję zgłębić filozofię programowania, a równocześnie zdobywać praktyczne umiejętności programistyczne na podstawowym poziomie. Starannie dobrany kod pokazuje możliwe zastosowania wybranych języków programowania. Pomoc w nauce stanowią też zadania do samodzielnego rozwiązania.

Komunikacja z AI. Dla początkujących

Katarzyna Majzel-Pośpiech

Naucz się promptować i skorzystaj w pełni z możliwości, jakie oferuje AI Jedni się jej obawiają, inni patrzą na nią z nadzieją. Sztuczna inteligencja, z angielskiego artificial intelligence (AI), to technologia, która oferuje niespotykane dotąd możliwości i imponującą wydajność. Jeśli w odpowiedni sposób zadać jej pytanie, jest w stanie precyzyjnie na nie odpowiedzieć i podsunąć rozwiązanie. Po otrzymaniu konkretnych wskazówek może wygenerować wysokiej jakości grafiki i filmy. Kluczowe jest, aby nauczyć się właściwie zadawać pytania i poprawnie formułować polecenia. Innymi słowy ― promptować. Prompt engineering polega na tworzeniu i optymalizowaniu promptów, czyli komend lub zapytań kierowanych do modeli sztucznej inteligencji. Promptowanie wymaga kreatywności, logicznego myślenia, znajomości języka i technologii AI, ale opanowanie jego reguł warte jest poświęconego czasu. W efekcie bowiem otrzymamy oczekiwane treści, grafiki, muzykę, wydajne wsparcie w kodowaniu i analizie danych. A to dopiero początek możliwości narzędzi takich jak ChatGPT czy Midjourney.  Jeśli: chcesz zrozumieć, na jakich zasadach działa sztuczna inteligencja pragniesz poznać reguły prompt engineeringu zależy Ci na tym, by spróbować swoich sił w promptowaniu zamierzasz tworzyć skuteczne i kreatywne prompty to książka właśnie dla Ciebie! Znajdziesz w niej wiedzę i inspiracje, które pozwolą Ci rozpocząć współpracę z dostępnymi na rynku modelami AI.

Large Language Models An Introduction. Understanding the Fundamentals and Applications of Generative AI

Mercury Learning and Information, Oswald Campesato

This book provides a comprehensive overview of large language models (LLMs) and generative AI, covering foundational principles, advanced concepts, and practical applications. It begins with an introduction to the generative AI landscape, examining key features, popular techniques, and its influence on industries like art, business, and technology. The book also explores prominent models like ChatGPT and GPT-4, detailing their architectures, capabilities, and applications in text generation, code assistance, and conversational AI.Additionally, the book traces the evolution of LLMs, particularly focusing on the BERT family and its wide-ranging applications in natural language processing, translation, and multilingual tasks. Readers will also gain expertise in prompt engineering, learning practical tips and examples to interact more effectively with LLMs.In later chapters, the book tackles advanced topics such as fine-tuning LLMs, working with SVG, and concepts like few-shot learning and reinforcement learning. It concludes with discussions on ethical issues, biases in generative AI, and emerging trends like AI’s integration with IoT, quantum computing, and neuromorphic computing. This guide equips professionals and enthusiasts with a thorough understanding of generative AI's present and future.

Learn OpenAI Whisper. Transform your understanding of GenAI through robust and accurate speech processing solutions

Josué R. Batista, Christopher Papile

As the field of generative AI evolves, so does the demand for intelligent systems that can understand human speech. Navigating the complexities of automatic speech recognition (ASR) technology is a significant challenge for many professionals. This book offers a comprehensive solution that guides you through OpenAI's advanced ASR system.You’ll begin your journey with Whisper's foundational concepts, gradually progressing to its sophisticated functionalities. Next, you’ll explore the transformer model, understand its multilingual capabilities, and grasp training techniques using weak supervision. The book helps you customize Whisper for different contexts and optimize its performance for specific needs. You’ll also focus on the vast potential of Whisper in real-world scenarios, including its transcription services, voice-based search, and the ability to enhance customer engagement. Advanced chapters delve into voice synthesis and diarization while addressing ethical considerations.By the end of this book, you'll have an understanding of ASR technology and have the skills to implement Whisper. Moreover, Python coding examples will equip you to apply ASR technologies in your projects as well as prepare you to tackle challenges and seize opportunities in the rapidly evolving world of voice recognition and processing.

Learning Game AI Programming with Lua. Leverage the power of Lua programming to create game AI that focuses on motion, animation, and tactics

David Young

Learning OpenCV 3 Computer Vision with Python. Unleash the power of computer vision with Python using OpenCV

Gionata Minichino, Joseph Howse, Gil Levi, Joe Minichino

Machine Learning: End-to-End guide for Java developers. Data Analysis, Machine Learning, and Neural Networks simplified

Boštjan Kaluža, Krishna Choppella, Uday Kamath

Machine Learning is one of the core area of Artificial Intelligence where computers are trained to self-learn, grow, change, and develop on their own without being explicitly programmed. In this course, we cover how Java is employed to build powerful machine learning models to address the problems being faced in the world of Data Science. The course demonstrates complex data extraction and statistical analysis techniques supported by Java, applying various machine learning methods, exploring machine learning sub-domains, and exploring real-world use cases such as recommendation systems, fraud detection, natural language processing, and more, using Java programming. The course begins with an introduction to data science and basic data science tasks such as data collection, data cleaning, data analysis, and data visualization. The next section has a detailed overview of statistical techniques, covering machine learning, neural networks, and deep learning. The next couple of sections cover applying machine learning methods using Java to a variety of chores including classifying, predicting, forecasting, market basket analysis, clustering stream learning, active learning, semi-supervised learning, probabilistic graph modeling, text mining, and deep learning.The last section highlights real-world test cases such as performing activity recognition, developing image recognition, text classification, and anomaly detection. The course includes premium content from three of our most popular books:[*]Java for Data Science[*]Machine Learning in Java [*]Mastering Java Machine LearningOn completion of this course, you will understand various machine learning techniques, different machine learning java algorithms you can use to gain data insights, building data models to analyze larger complex data sets, and incubating applications using Java and machine learning algorithms in the field of artificial intelligence.