“…The book will also benefit data scientists, product managers, and basically any role wherein you are expected to gather data insights and develop business strategies using SQL as a language. …”

“…Data engineers, data scientists, business intelligence developers, and database administrators who want to learn how to design end-to-end data solutions and get a bird's-eye view of the entire data platform will find this book useful. …”

“…About The Author Nikolai Schuler: Nikolai Schuler, as a data scientist and BI consultant, believes that the data world benefits from new tools and technologies, but it is extremely difficult to get trained in the field as practical courses with quality content are rare or are structured incompatible with a busy working life. …”

“…This unique collaboration allows access to hundreds of scientists, architects, urbanists, multilaterals, policymakers, non-profit leaders, and grassroots organizers. …”

“…What you will learn Grasp the fundamentals of the OpenAI API Navigate the API's capabilities and limitations of the API Set up the OpenAI API with step-by-step instructions, from obtaining your API key to making your first call Explore advanced features such as system messages, fine-tuning, and the effects of different parameters Integrate the OpenAI API into existing applications and workflows to enhance their functionality with AI Design and build applications that fully harness the power of ChatGPT Who this book is for This book is perfect for developers, data scientists, AI/tech enthusiasts, citizen developers, and no-code aficionados keen on using and mastering the OpenAI API. …”

“…What you will learn Master the fundamentals of active machine learning Understand query strategies for optimal model training with minimal data Tackle class imbalance, concept drift, and other data challenges Evaluate and analyze active learning model performance Integrate active learning libraries into workflows effectively Optimize workflows for human labelers Explore the finest active learning tools available today Who this book is for Ideal for data scientists and ML engineers aiming to maximize model performance while minimizing costly data labeling, this book is your guide to optimizing ML workflows and prioritizing quality over quantity. …”

“…Additionally, data scientists and analysts who want to enhance their practical knowledge of ML systems engineering, as well as AI/ML product managers and risk officers who want to gain an understanding of ML solutions and AI risk management, will also find this book useful. …”

“…About The Author Bert Gollnick: Bert Gollnick is a proficient data scientist with substantial domain knowledge in renewable energies, particularly wind energy. …”

“…What you will learn Get an overview of ML and working with data and models in Python using scikit-learn Explore decision trees, ensemble learning, gradient boosting, DART, and GOSS Master LightGBM and apply it to classification and regression problems Tune and train your models using AutoML with FLAML and Optuna Build ML pipelines in Python to train and deploy models with secure and performant APIs Scale your solutions to production readiness with AWS Sagemaker, PostgresML, and Dask Who this book is for This book is for software engineers aspiring to be better machine learning engineers and data scientists unfamiliar with LightGBM, looking to gain in-depth knowledge of its libraries. …”

“…What you will learn Convert text into numerical values such as bag-of-word, TF-IDF, and word embedding Use various NLP techniques with Gensim, including Word2Vec, Doc2Vec, LSA, FastText, LDA, and Ensemble LDA Build topical modeling pipelines and visualize the results of topic models Implement text summarization for legal, clinical, or other documents Apply core NLP techniques in healthcare, finance, and e-commerce Create efficient chatbots by harnessing Gensim's NLP capabilities Who this book is for This book is for data scientists and professionals who want to become proficient in topic modeling with Gensim. …”

“…Datasets often arrive in different conditions and formats, demanding considerable time from analysts, engineers, and scientists to process and uncover insights. The complexity of the data life cycle often hinders teams and organizations from extracting the desired value from their data assets. …”

“…The book avoids twisted technical, engineering, or data science aspects, making it accessible and insightful for data engineers and data scientists to gain a wider understanding of enterprise data needs and challenges…”

“…You'll see how the simple act of removing personally identifiable information (PII) from a dataset lowers the risk of social engineering attacks.By the end of this machine learning book, you'll have an increased awareness of the various attacks and the techniques to secure your ML systems effectively.What You Will Learn:Explore methods to detect and prevent illegal access to your systemImplement detection techniques when access does occurEmploy machine learning techniques to determine motivationsMitigate hacker access once security is breachedPerform statistical measurement and behavior analysisRepair damage to your data and applicationsUse ethical data collection methods to reduce security risksWho this book is for:Whether you're a data scientist, researcher, or manager working with machine learning techniques in any aspect, this security book is a must-have . …”

“…Author Alessandro Negro explores examples from real-world applications that connect GraphML concepts to real world tasks. about the audience For readers comfortable with machine learning basics. about the author Alessandro Negro is Chief Scientist at GraphAware. He has been a speaker at many conferences, and holds a PhD in Computer Science. …”

“…Serrano is a research scientist in quantum artificial intelligence. Previously, he was a Machine Learning Engineer at Google and Lead Artificial Intelligence Educator at Apple. …”

“…Serrano is a research scientist in quantum artificial intelligence. Previously, he was a Machine Learning Engineer at Google and Lead Artificial Intelligence Educator at Apple. …”

“…Author Alessandro Negro explores examples from real-world applications that connect GraphML concepts to real world tasks. about the audience For readers comfortable with machine learning basics. about the author Alessandro Negro is Chief Scientist at GraphAware. He has been a speaker at many conferences, and holds a PhD in Computer Science. …”

“…What you will learn Explore core concepts and applications of Stable Diffusion and set up your environment for success Refine performance, manage VRAM usage, and leverage community-driven resources like LoRAs and textual inversion Harness the power of ControlNet, IP-Adapter, and other methodologies to generate images with unprecedented control and quality Explore developments in Stable Diffusion such as video generation using AnimateDiff Write effective prompts and leverage LLMs to automate the process Discover how to train a Stable Diffusion LoRA from scratch Who this book is for If you're looking to gain control over AI image generation, particularly through the diffusion model, this book is for you. Moreover, data scientists, ML engineers, researchers, and Python application developers seeking to create AI image generation applications based on the Stable Diffusion framework can benefit from the insights provided in the book…”

“…What you will learn Understand the core components of blockchain transactions and blocks Identify reliable sources of on-chain and off-chain data to build robust datasets Understand key Web3 business questions and how data science can offer solutions Build your skills to create and query NFT- and DeFi-specific datasets Implement a machine learning toolbox with real-world use cases in the Web3 space Who this book is for This book is designed for data professionals--data analysts, data scientists, or data engineers-- and business professionals, aiming to acquire the skills for extracting data from the Web3 ecosystem, as it demonstrates how to effectively leverage data tools for in-depth analysis of blockchain transactional data. …”

“…Computer scientists are drawn to the field as a powerful site for the development and application of advanced computational techniques. …”