“…By the end of this book, you will have grasped how to build your own Markov and hidden Markov models on complex datasets in order to apply them to projects.What you will learnExplore a balance of both theoretical and practical aspects of HMMImplement HMMs using different datasets in Python using different packagesUnderstand multiple inference algorithms and how to select the right algorithm to resolve your problemsDevelop a Bayesian approach to inference in HMMsImplement HMMs in finance, natural language processing (NLP), and image processingDetermine the most likely sequence of hidden states in an HMM using the Viterbi algorithmWho this book is forHands-On Markov Models with Python is for you if you are a data analyst, data scientist, or machine learning developer and want to enhance your machine learning knowledge and skills. …”

“…Finally, you'll work through examples to help you solve typical business problems.By the end of this book, you'll be able to build end-to-end machine learning services using a variety of techniques and design your own processes for consistently performant machine learning engineering.What You Will Learn:Find out what an effective ML engineering process looks likeUncover options for automating training and deployment and learn how to use themDiscover how to build your own wrapper libraries for encapsulating your data science and machine learning logic and solutionsUnderstand what aspects of software engineering you can bring to machine learningGain insights into adapting software engineering for machine learning using appropriate cloud technologiesPerform hyperparameter tuning in a relatively automated wayWho this book is for:This book is for machine learning engineers, data scientists, and software developers who want to build robust software solutions with machine learning components. …”

“…By the end of this Azure book, you'll be able to use Azure Databricks to streamline different processes involved in building data-driven apps.What you will learnRead and write data from and to various Azure resources and file formatsBuild a modern data warehouse with Delta Tables and Azure Synapse AnalyticsExplore jobs, stages, and tasks and see how Spark lazy evaluation worksHandle concurrent transactions and learn performance optimization in Delta tablesLearn Databricks SQL and create real-time dashboards in Databricks SQLIntegrate Azure DevOps for version control, deploying, and productionizing solutions with CI/CD pipelinesDiscover how to use RBAC and ACLs to restrict data accessBuild end-to-end data processing pipeline for near real-time data analyticsWho this book is forThis recipe-based book is for data scientists, data engineers, big data professionals, and machine learning engineers who want to perform data analytics on their applications. …”

“…What you will learnApply ML methodologies to solve business problemsDesign a practical enterprise ML platform architectureImplement MLOps for ML workflow automationBuild an end-to-end data management architecture using AWSTrain large-scale ML models and optimize model inference latencyCreate a business application using an AI service and a custom ML modelUse AWS services to detect data and model bias and explain modelsWho this book is forThis book is for data scientists, data engineers, cloud architects, and machine learning enthusiasts who want to become machine learning solutions architects. …”

“…But, we aim to introduce psychologists and social scientists to this challenging new research area, encouraging them, at the same time, to consider its promising results. …”

“…What You'll Learn: Choose the right Microsoft product for your machine learning solution Create and manage Microsoft’s tool environments for development, testing, and production of a machine learning project Implement and deploy supervised and unsupervised learning in Microsoft products Set up Microsoft Power BI, Azure Data Lake, SQL Server, Stream Analytics, Azure Databricks, and HD Insight to perform machine learning Set up a data science virtual machine and test-drive installed tools, such as Azure ML Workbench, Azure ML Server Developer, Anaconda Python, Jupyter Notebook, Power BI Desktop, Cognitive Services, machine learning and data analytics tools, and more Architect a machine learning solution factoring in all aspects of self service, enterprise, deployment, and sharing This book is for data scientists, data analysts, developers, architects, and managers who want to leverage machine learning in their products, organization, and services, and make educated, cost-saving decisions about their ML architecture and tool set. …”

“…You'll learn about machine learning algorithms like a data scientist, learning along the way. This process means that you'll find that your new skills stick, embedded as best practice. …”

“…Machine and deep learning practitioners, research scholars, and data scientists would also benefit from this course. As prerequisites, no prior recommender systems, ML, data analysis knowledge is needed. …”

“…Deep learning practitioners, research scholars, and data scientists will also benefit from the course. The prerequisites include a basic to intermediate knowledge of Python and Pandas library. …”

“…This course can benefit ML/DL practitioners, research scholars, and data scientists researching chatbots. No prior knowledge of chatbots, ML, DL, Amazon Lex, data analysis, or mathematics is required. …”

“…His expertise in online advertising and digital media includes work as both a data scientist and big data engineer. He has created deep learning models for prediction and has experience in recommendation systems using reinforcement learning and collaborative filtering. …”

“…His expertise in online advertising and digital media includes work as both a data scientist and big data engineer. He has created deep learning models for prediction and has experience in recommendation systems using reinforcement learning and collaborative filtering. …”

“…What you will learn Use Adobe Acrobat Pro efficiently through shortcuts and preferences Expand your knowledge of the functions that you already use Understand the connection between PDFs, Acrobat, and other applications Find out about unique settings in Adobe InDesign to create high-quality fully featured PDFs Address legal concerns for information published in a digital format Confidently move away from the use of ink and paper and help preserve physical resources Who this book is for This book is for anyone working with PDFs on a daily basis, including skilled professionals such as analysts, administrators, architects, engineers, scientists, lawyers, and anyone who can be described as communications workers, including but not limited to artworkers, researchers, technical writers, and accessibility workers who routinely work with PDF and some version of Acrobat…”

“…This course will benefit individuals interested in building customized chatbots for their applications--AI practitioners, chatbot developers, research scholars, data scientists, and so on. About The Author AI Sciences: AI Sciences are experts, PhDs, and artificial intelligence practitioners, including computer science, machine learning, and Statistics. …”

“…What you will learn Build efficient queries by reducing the data being returned Manipulate your data and format it for easier consumption Form common table expressions and window functions to solve complex business issues Understand the impact of SQL security on your results Understand and use query plans to optimize your queries Understand the impact of indexes on your query performance and design Work with data lake data and JSON in SQL queries Organize your queries using Jupyter notebooks Who this book is for This book is for SQL developers, data analysts, report writers, data scientists, and other data gatherers looking to expand their skills for complex querying as well as for building more efficient and performant queries. …”

“…What you will learn Master the fundamentals steps of data science through practical examples Bridge the gap between math and programming using advanced statistics and ML Harness probability, calculus, and models for effective data control Explore transformative modern ML with large language models Evaluate ML success with impactful metrics and MLOps Create compelling visuals that convey actionable insights Quantify and mitigate biases in data and ML models Who this book is for If you are an aspiring novice data scientist eager to expand your knowledge, this book is for you. …”

“…What you will learn Scale RAG pipelines to handle large datasets efficiently Employ techniques that minimize hallucinations and ensure accurate responses Implement indexing techniques to improve AI accuracy with traceable and transparent outputs Customize and scale RAG-driven generative AI systems across domains Find out how to use Deep Lake and Pinecone for efficient and fast data retrieval Control and build robust generative AI systems grounded in real-world data Combine text and image data for richer, more informative AI responses Who this book is for This book is ideal for data scientists, AI engineers, machine learning engineers, and MLOps engineers. …”

“…Whether you're an administrator, engineer, architect, developer, analyst, aspiring data scientist, or a non-technical enthusiast interested in learning data concepts, this book is for you. …”

“…This is a must-have resource for machine learning developers and data scientists working on ML projects. IT administrators, DevOps, and security engineers required to secure and monitor Azure workloads will also benefit from this book, as the chapters cover everything from implementation to deployment, AI attack prevention, and recovery…”

“…What you will learn Understand the science behind malware data and its management lifecycle Explore anomaly detection with signature and heuristics-based methods Analyze data to uncover relationships between data points and create a network graph Discover methods for reverse engineering and analyzing malware Use ML, advanced analytics, and data mining in malware data analysis and detection Explore practical insights and the future state of AI's use for malware data science Understand how NLP AI employs algorithms to analyze text for malware detection Who this book is for This book is for cybersecurity experts keen on adopting data-driven defense methods. Data scientists will learn how to apply their skill set to address critical security issues, and compliance officers navigating global regulations like GDPR and CCPA will gain indispensable insights. …”