Bits of Data Science

understanding deep learning 📚 Book

Very cool cookbook here PDF extractor, calendar agent, data analyst, financial agent & more docs: https://docs.cohere.com/docs/multi-step-tool-use cookbook: https://github.com/cohere-ai/notebooks/tree/main?tab=readme-ov-file#agents

Core Python Applications Programming 📚 Book

Machine Learning Engineering Open Book 📚 Book

Artificial Intelligence and Games (2nd Edition) 📚 Book

DevOps for Data Science 📚 Book

Tech Interview Handbook 📚 Book

Fundamentals of Data Engineering 📚 Book

Data-Science-Interview-Resources 🟡 Machine Learning interview resources @datascienceiot

Introduction to Machine Learning 📚 Book

Complete Tableau Topics for Data Analysts 👇👇 1. Introduction to Tableau - Overview of Tableau products (Desktop, Server, Online, Public, Reader) - Installing and setting up Tableau 2. Connecting to Data - Types of data connections (Excel, SQL, CSV, etc.) - Connecting to live data vs. Extracts - Data source page and data preparation (Joins, Blends, Unions) 3. Data Transformation and Preparation - Data cleaning and shaping - Pivoting and splitting data - Data Interpreter - Calculated fields - Level of Detail (LOD) expressions - Using Tableau Prep for data preparation 4. Building Basic Visualizations - Bar charts, line charts, pie charts - Scatter plots, histograms, bullet graphs - Geographic maps and filled maps 5. Advanced Visualizations - Dual-axis and blended axes - Combined charts (bar-in-bar, line-in-bar) - Treemaps, heat maps, and bubble charts - Gantt charts, box plots, waterfall charts - Motion charts and control charts 6. Dashboard Creation - Designing effective dashboards - Using containers and layout techniques - Interactive dashboard elements (filters, parameters, actions) - Device-specific dashboards 7. Table Calculations - Basics of table calculations - Quick table calculations (percent of total, running total) - Custom table calculations (calculating differences, percent change) 8. Advanced Analytics - Trend lines, reference lines, and reference bands - Forecasting and clustering - Integrating R and Python for advanced analytics 9. Interactivity and User Controls - Filters (dimension filters, measure filters, context filters) - Parameters (creating and using parameters) - Dashboard actions (filter actions, highlight actions, URL actions) 10. Performance Optimization - Extracts vs. live connections - Data source optimization techniques - Performance recording and analysis 11. Sharing and Collaboration - Publishing workbooks to Tableau Server/Online - Tableau Public for sharing visualizations - Managing permissions and user access - Embedding visualizations in web pages 12. Tableau Extensions and API - Using Tableau extensions for additional functionality - Introduction to Tableau JavaScript API for embedding and interacting with visualizations 13. Best Practices and Case Studies - Best practices for data visualization and storytelling - Real-world case studies and applications of Tableau 14. Certification Preparation - Preparing for Tableau Desktop Specialist, Certified Associate, and Certified Professional exams Best Resources to learn Tableau: https://topmate.io/analyst/890464 Like this post if you want me to continue this Tableau series 👍♥️ Share with credits: https://t.me/sqlspecialist Hope it helps :)

Obey the Testing Goat! TDD for the Web, with Python, Selenium, Django, JavaScript and pals... 📓Book @pythonlbooks

Introduction to Machine Learning 📚 Book @datascienceiot

Algorithm Design and Analysis 📓 Book @datascienceiot