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https://www.analyticsvidhya.com/learning-paths-data-science-business-analytics-business-intelligence-big-data/learning-path-data-science-python/ Comprehensive learning path – #Data_Science in Python Journey from a Python noob to a Kaggler on Python So, you want to become a data scientist or may be you are already one and want to expand your tool repository. You have landed at the right place. The aim of this page is to provide a comprehensive learning path to people new to python for data analysis. This path provides a comprehensive overview of steps you need to learn to use Python for #data_analysis. If you already have some background, or don’t need all the components, feel free to adapt your own paths and let us know how you made changes in the path. You can also check the mini version of this learning path #Deep_Learning

http://mdp.cdm.depaul.edu/DePy2016 3rd Annual #Conference on #Python applications in #Data_Analysis, #Machine_Learning, and Web May 6, 7 DePaul University - Room LL105 14 E Jackson Blvd Chicago IL 60604, USA

🔥 20 Step-by-Step Data Analysis Projects with Python Code Below are popular data analysis projects from Kaggle, Github, and Medium users. They will: - Help you gain skills in working with real data - Introduce you to Python libraries for data analysis - Inspire you for your own data analysis projects #data_analyst#data_analysis#data_projects ☕Coffee Shop Sales Analysis ⚽ FIFA World Cup Data Analysis ⚡️ADIDAS Sales Analysis 📱Netflix Data Analysis (1) ⚡️ Zomato Data Analysis 🍫 Product Sales Analysis 🚕 Uber Rides Data Analysis 👀Smartwatch Data Analysis 🤑Financial Budget Analysis 📱Netflix Data Analysis (2) 🎮 Video Game Sales Analysis 🤓 Is There a Trend of Increasing Geek Girls? 🏆 Let's Discover More About the Olympic Games! 📉Marketing Analysis 🐶Animal Shelter Data Analysis 📱 Amazon Data Analysis 💲Billionaire Data Analysis 📱 Credit Card Data Analysis 😏Pokemon Data Analysis 📱Spotify Data Analysis. What Does It Take to Hit the Charts #DataAnalyst#DataAnalytics#DataAnalysis#data_analyst#python If you find this content useful, give it a🔥!

#python#agent_framework#data_analysis#deep_research#deep_search#llms#multi_agent_system#nlp#public_opinion_analysis#python3#sentiment_analysis You can use the "Weibo Public Opinion Analysis System" (called "微舆") to automatically analyze public opinion from over 30 major social media platforms and millions of comments. It uses AI agents working together to monitor, search, analyze text and videos, and generate detailed reports based on real-time data. The system supports easy setup, custom models, and integration with your own databases, helping you understand public sentiment, trends, and make better decisions. It offers continuous monitoring, deep multi-angle analysis, and flexible report generation, all accessible by simply asking questions like chatting. This saves you time and gives clear insights into public opinion dynamics. https://github.com/666ghj/BettaFish

#python#data_analysis#dingtalk_robot#docker#feishu_robot#hot_news#mail#mcp#mcp_server#news#ntfy#python#telegram_bot#trending_topics#wechat_robot TrendRadar is a lightweight, easy-to-deploy tool that gathers trending topics from 11+ major platforms like Zhihu, Douyin, and Baidu in just 30 seconds. It lets you set custom keywords to filter only news you care about, eliminating information overload. The tool offers three smart notification modes—daily summaries, current rankings, or incremental alerts—and supports multiple channels including WeChat Work, Feishu, DingTalk, Telegram, and email. You can customize how trends are ranked using a personalized algorithm that weighs ranking position, frequency, and hotness. With GitHub Pages for web reports, Docker support, and AI-powered analysis through MCP protocol, TrendRadar transforms scattered platform algorithms into one unified, user-controlled news feed tailored to your interests. https://github.com/sansan0/TrendRadar

#other#automl#chatgpt#data_analysis#data_science#data_visualization#data_visualizations#deep_learning#gpt#gpt_3#jax#keras#machine_learning#ml#nlp#python#pytorch#scikit_learn#tensorflow#transformer This is a comprehensive, regularly updated list of 920 top open-source Python machine learning libraries, organized into 34 categories like frameworks, data visualization, NLP, image processing, and more. Each project is ranked by quality using GitHub and package manager metrics, helping you find the best tools for your needs. Popular libraries like TensorFlow, PyTorch, scikit-learn, and Hugging Face transformers are included, along with specialized ones for time series, reinforcement learning, and model interpretability. This resource saves you time by guiding you to high-quality, actively maintained libraries for building, optimizing, and deploying machine learning models efficiently. https://github.com/ml-tooling/best-of-ml-python

#python#agent_skills#ai_scientist#bioinformatics#chemoinformatics#claude#claude_skills#claudecode#clinical_research#computational_biology#data_analysis#drug_discovery#genomics#materials_science#metabolomics#proteomics#scientific_computing#scientific_visualization Claude Scientific Skills offers 148+ ready-to-use tools for AI agents like Cursor or Claude Code, covering biology, chemistry, drug discovery, clinical research, ML, and 250+ databases (PubMed, ChEMBL, etc.). Easy setup: clone the GitHub repo and copy folders to your skills directory for automatic use in complex workflows like single-cell analysis or virtual screening. You save days on setup, get reliable code, and run multi-step science faster on your desktop. https://github.com/K-Dense-AI/claude-scientific-skills

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