#Data Science

Explore a comprehensive compilation of over 180 YouTube channels providing insights into data science, machine learning, AI, programming, and software engineering. This collection serves as a valuable resource for students, professionals, and hobbyists seeking to broaden their knowledge with content ranging from tutorials to podcast discussions. Regular updates and community input ensure the list's accuracy and relevance, appealing to those interested in data engineering, statistics, web development, and cybersecurity. Discover specialized content in programming languages such as Python, R, and C++ to enhance your learning experience.

Discover an open-source data science repository with resources for learning and applying skills in practical scenarios. Access beginner to advanced tutorials, courses, and essential tools such as Python and R. Explore curated pathways like MOOCs, free courses, and intensive programs, equipped with a comprehensive toolbox including algorithms, machine learning packages, and visualization tools. Expand knowledge with literature, media, and community resources for a thorough understanding of data science.

Explore how leading industries apply data science and machine learning in practical production scenarios. Understand the implementation of ML projects through problem framing, techniques, results, and scientific backing. Access curated resources on vital subjects like data quality, engineering, and feature stores to gauge real-world ML project returns.

Aquila DB serves as a neural search engine enabling data scientists and machine learning engineers to perform efficient k-NN retrieval on latent vectors and JSON metadata. This tool is language-agnostic and minimally dependent, designed to facilitate neural information retrieval applications. Currently in alpha, it supports semantic search in production and encourages community contributions. Best suited for image metadata and large datasets, but not intended for use as a document database.

Explore insights into developing essential software engineering skills with an emphasis on Python and generative AI. Updated monthly, this project explores key competencies in areas like data structures, algorithms, Linux, version control, database management, backend development, system design, frontend basics, and specialized fields such as machine learning and NLP. Designed for individuals aiming to enhance expertise in adjacent technologies methodically, from Python data tools to advanced AI techniques.

Discover detailed charts and guides to become an AI, data science, or machine learning professional. Benefit from interactive resources and updates supported by AMAI GmbH, designed for clarity in educational paths.

The directory showcases various Telegram groups, channels, and bots designed for programmers and IT enthusiasts. Explore topics from programming languages and frameworks to DevOps, cybersecurity, and machine learning. An essential tool for IT experts seeking updates and discussions. Contributions are welcomed to keep the list relevant. Follow the official channel and join the chat for more insights.

This repository hosts a diverse collection of small-scale projects centered around Deep Learning and Data Science, complete with practical implementations and engaging visualizations. It builds on Medium articles to demystify complex neural network challenges, including overseeing practical applications like visualizing neural networks, understanding overfitting, optimization, and object detection. Users can deepen their insights into convolutional neural networks and explore tools for explicating image classification results.

This guide offers a multitude of solved problems covering various AI and deep learning topics, aiding data scientists and job seekers in mastering AI concepts necessary for interviews. With detailed explanations and problem-solving strategies, it serves as a valuable reference for enhancing technical knowledge and interview readiness.

Cookiecutter Data Science provides a standardized project structure with v2 extending cookiecutter's functionalities for Python 3.8+. Simple installation via pipx ensures quick setup with the ccds tool. It supports both new and legacy templates, ideal for standardizing workflows, complete with documentation and open for contributions.

The course addresses computational linear algebra fundamentals crucial for data science, highlighting speed and precision. Using Python and Jupyter Notebooks, learners explore key libraries—Scikit-Learn, Numpy, and PyTorch—through practical exercises like topic modeling and health predictions. Gain insights into methodologies such as SVD and PCA, supported by video materials and forum discussions, enhancing practical matrix computation skills for industry applications.

This repository provides a comprehensive array of resources for individuals pursuing self-directed learning in machine learning. By utilizing publicly shared online lectures and blogs, it supports independent learners. The repository includes a curated selection of video lectures on Python programming, data analysis, visualization, and foundational math concepts, featuring both beginner and advanced topics from prominent platforms and educators like Andrew Ng and Stanford. It also includes practical tutorials for tools such as Scikit-Learn and PyTorch, promoting a gradual and effective learning of machine learning methods.

Engage in a 100-day program designed to deepen understanding of machine learning algorithms, covering initial topics like data preprocessing and linear regression, progressing to advanced subjects such as SVM and deep learning. Daily lessons include practical exercises, theoretical insights, and resources, aimed at professionals and enthusiasts seeking to enhance their skills in algorithms like decision trees and neural networks.

Discover a wide array of resources for various programming languages and technologies, including Agile development, Android programming, and Machine Learning. This curated compilation provides essential tools and tutorials for both novices and seasoned developers. Gain insights from leading developer blogs and narratives. Access latest tech updates with material on frameworks such as Angular, Django, and React, along with languages like Python and JavaScript. Empower your development journey with practical projects and engaging courses, positioning this resource as indispensable for career advancement.

Discover a curated collection of data science interview questions and answers, neatly categorized by topics such as machine learning, deep learning, statistics, and more. This repository serves as an excellent resource for refreshing data science fundamentals and effectively preparing for interviews by familiarizing with potential questions and their answers. The content is regularly updated to ensure ongoing relevance, making it a valuable tool for refining skills across different data science domains.

Discover a rich collection of Jupyter Notebooks and code in Python, HTML5, and D3.JS, tailored for data scientists looking to explore and learn about data collection, preprocessing, analysis, visualization, and narrative techniques. Including insights on sentiment analysis, scikit-learn and PyCaret workflows, and innovative visualization methods with Altair and Plotly, this project offers comprehensive resources available across multiple platforms, backed by detailed documentation and curated tutorials on Medium.