MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 20 Lessons (2h 1m) | Size: 391.7 MB
Supabase is an open-source tool for rapidly building application backends with real-time data and authentication. In this course, you'll learn the fundamentals of Supabase. You'll learn how to model complex data using PostgreSQL and SQL, build authentication flows with Oauth, and add real-time data to a Next.js application to build a fully-featured chat application, similar to Discord.

Hi-C Data Analysis
English | 2022 | ISBN: 1071613898 | 355 Pages | PDF | 12 MB
This volume details a comprehensive set of methods and tools for Hi-C data processing, analysis, and interpretation. Chapters cover applications of Hi-C to address a variety of biological problems, with a specific focus on state-of-the-art computational procedures adopted for the data analysis. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls.

Foundations of Data Science for Engineering Problem Solving
English | 2022 | ISBN: 9811651590 | 125 Pages | PDF | 4 MB
This book is one-stop shop which offers essential information one must know and can implement in real-time business expansions to solve engineering problems in various disciplines. It will also help us to make future predictions and decisions using AI algorithms for engineering problems. Machine learning and optimizing techniques provide strong insights into novice users. In the era of big data, there is a need to deal with data science problems in multidisciplinary perspective. In the real world, data comes from various use cases, and there is a need of source specific data science models. Information is drawn from various platforms, channels, and sectors including web-based media, online business locales, medical services studies, and Internet. To understand the trends in the market, data science can take us through various scenarios. It takes help of artificial intelligence and machine learning techniques to design and optimize the algorithms. Big data modelling and visualization techniques of collected data play a vital role in the field of data science. This book targets the researchers from areas of artificial intelligence, machine learning, data science and big data analytics to look for new techniques in business analytics and applications of artificial intelligence in recent businesses.

Epidemics: Models and Data using R by Ottar N. Bjørnstad
English | EPUB | 2018 | 318 Pages | ISBN : 3319974866 | 134.9 MB
This book is designed to be a practical study in infectious disease dynamics. The book offers an easy to follow implementation and analysis of mathematical epidemiology. The book focuses on recent case studies in order to explore various conceptual, mathematical, and statistical issues. The dynamics of infectious diseases shows a wide diversity of pattern. Some have locally persistent chains-of-transmission, others persist spatially in 'consumer-resource metapopulations'. Some infections are prevalent among the young, some among the old and some are age-invariant.

Data Wrangling with R by Bradley C. Boehmke, Ph.D.
English | EPUB | 2016 | 237 Pages | ISBN : 3319455982 | 1.1 MB
This guide for practicing statisticians, data scientists, and R users and programmers will teach the essentials of preprocessing: data leveraging the R programming language to easily and quickly turn noisy data into usable pieces of information. Data wrangling, which is also commonly referred to as data munging, transformation, manipulation, janitor work, etc., can be a painstakingly laborious process.

Data Management, Analytics and Innovation: Proceedings of ICDMAI 2019, Volume 1 by Neha Sharma
English | PDF | 2019 | 480 Pages | ISBN : 9813299487 | 21.8 MB
This book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence and data analytics, along with advances in network technologies. It addresses state-of-the-art topics and discusses challenges and solutions for future development. Gathering original, unpublished contributions by scientists from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry.

Big Data Architect's Handbook:
A guide to building proficiency in tools and systems used by leading big data experts
English | 2018 | ISBN: 1788835824 | 488 Pages | EPUB | 15 MB

Packt - The Microsoft Excel Data Analysis Toolkit Bundl-XQZT
English | Size: 5.82 GB
Category: Excel

Linkedin Learning - Data Science Foundations Knowledge Graphs-XQZT
English | Size: 118.77 MB
Category: Tutorial

English | 2021 | ISBN: 1492075736 | 346 pages | True PDF | 8.94 MB
Fairness is an increasingly important topic as machine learning and AI more generally take over the world. While this is an active area of research, many realistic best practices are emerging at all steps along the data pipeline, from data selection and preprocessing to blackbox model audits. This book will guide you through the technical, legal, and ethical aspects of making your code fair and secure while highlighting cutting edge academic research and ongoing legal developments related to fairness and algorithms.
There is mounting evidence that the widespread deployment of machine learning and artificial intelligence in business and government is reproducing the same biases we are trying to fight in the real world. For this reason, fairness is an increasingly important consideration for the data scientist. Yet discussions of what fairness means in terms of actual code are few and far between. This code will show you how to code fairly as well as cover basic concerns related to data security and privacy from a fairness perspective.