Data Science & Machine Learning

𝗡𝗲𝘄 𝗔𝗜 𝗧𝗼𝗼𝗹 𝗔𝗹𝗲𝗿𝘁: 𝗚𝗶𝗴𝗮𝗖𝗵𝗮𝘁 𝟯.𝟱 𝗥𝗲𝗮𝘀𝗼𝗻𝗶𝗻𝗴 🚀 Want to solve complex coding & math problems faster? This new open-source LLM actually thinks before it answers! 💡 Built on GigaChat 3.5 Ultra: explores multiple step-by-step reasoning paths & uses automated verification 💡 Autonomously plans multi-step actions & decides when to call external tools 💡 Highly efficient: Linear attention retains key points, using 37% fewer tokens than DeepSeek V4 Flash Preview 📈 Massive benchmark gains over non-reasoning versions: • IFBench: 44 → 77 • Natural Plan: 64 → 80 • LiveCodeBench v6: 56 → 85 🎯 Perfect for Software Engineers, Data Scientists, and Students preparing for technical interviews! 🔗 𝗗𝗼𝘄𝗻𝗹𝗼𝗮𝗱 𝘄𝗲𝗶𝗴𝗵𝘁𝘀 𝗵𝗲𝗿𝗲 👇 (MIT License): fp8 | bf16

The 5 FREE Must-Read Books for Every AI Engineer 1. Practical Deep Learning A hands-on course using Python, PyTorch, and fastai to build, train, and deploy real-world deep learning models through interactive notebooks and applied projects. 2. Neural Networks and Deep Learning An intuitive and code-rich introduction to building and training deep neural networks from scratch, covering key topics like backpropagation, regularization, and hyperparameter tuning. 3. Deep Learning A comprehensive, math-heavy reference on modern deep learning—covering theory, core architectures, optimization, and advanced concepts like generative and probabilistic models. 4. Artificial Intelligence: Foundations of Computational Agents Explains AI through computational agents that learn, plan, and act, blending theory, Python examples, and ethical considerations into a balanced and modern overview. 5. Ethical Artificial Intelligence Explores how to design safe AI systems by aligning them with human values and preventing issues like self-delusion, reward hacking, and unintended harmful behavior ✅ Double Tap ❤️ For More

✅ Excel for Data Analysis 📊📈 👉 Excel is one of the most widely used tools in: ✔ Data Analysis ✔ Business Reporting ✔ Finance ✔ Operations Even today, Excel is heavily used in companies worldwide. 🔹 1. Why Excel is Important? ✔ Easy to use ✔ Fast data analysis ✔ Great for reporting ✔ Common interview skill 🔥 2. Important Excel Features for Data Analysis ✔ Formulas & Functions ✔ Sorting & Filtering ✔ Conditional Formatting ✔ Pivot Tables ✔ Charts & Dashboards 🔹 3. Basic Formulas ⭐ ✅ SUM Adds values. =SUM(A1:A10) ✅ AVERAGE Finds average value. =AVERAGE(A1:A10) ✅ COUNT Counts numbers. =COUNT(A1:A10) ✅ MAX & MIN =MAX(A1:A10) =MIN(A1:A10) 🔹 4. IF Function ⭐ Used for conditions. =IF(A1>50,"Pass","Fail") 🔹 5. VLOOKUP ⭐ Searches for values in tables. =VLOOKUP(101,A2:D10,2,FALSE) 👉 Very important interview topic. 🔹 6. Pivot Tables ⭐ Used for: ✔ Summarizing data ✔ Grouping information ✔ Quick analysis Example: 👉 Total sales by region. 🔹 7. Conditional Formatting Highlights important values. Examples: ✔ High sales → Green ✔ Low sales → Red 🔹 8. Charts in Excel Popular charts: ✔ Bar Chart ✔ Pie Chart ✔ Line Chart ✔ Combo Chart 🔹 9. Why Excel Still Matters? ✔ Used in almost every company ✔ Impor

Your Data Science degree just got an AI update. Yeah. Things are moving fast. Python. SQL. Machine Learning. Deep Learning. MLOps. And now GenAI, LLMs, RAG & AI-powered workflows. An 8-month program with 20+ industry projects and live weekend classes. Maybe Data Science was just the beginning. https://lp.pwskills.com/data-science-ai-online-program-pw-skills?utm_source=telegram&utm_medium=influencer&utm_campaign=deepakAugDS