IIT Madras BS in Data Science Programme’s Post

🎯Journey has started . CHALLENGE -COMPLETE ML AND MLOPS Yes I have started the most exciting journey of my learning path . Here I will be uploading my journey of getting good hand on ML AND AI , and also I will be sharing all my experience and learning . Join me in the exciting journey and also share your thoughts in the comment section💡. Day 1 - Probability distribution function , cumulative function analysis on random variable #coding #datascience #Machinelearning #learnwithme #ai

🚀 Exciting News! On July 25th, incredible session on AI Explained: Productionizing GenAI at Scale! 🤖✨ Join as we explore the latest advancements, innovative applications, and future possibilities of AI-generated content. We'll dive into how Generative AI is transforming industries, from creative art generation to sophisticated language models in customer service. Don’t miss this opportunity to engage with brilliant minds, share insights, and push the boundaries of what's possible with AI. Mark your calendars and be part of the conversation! #GenerativeAI #AI #MachineLearning #Innovation #TechTalk #ArtificialIntelligence

I’m thrilled to have completed the Machine Learning certification from Coding Ninjas! #MachineLearning #ArtificialIntelligence #CodingNinjas #LifelongLearning #DataScience #AI #TechSkills

Unpopular opinion: If you're a healthcare professional looking to learn AI, do not opt for an "AI In Healthcare" course. Instead: 1. Study foundational Machine learning and Deep learning approaches 2. Learn the maths behind AI models 3. Learn to code (start with Python) and build models 4. Read the latest research on ArXiv 5. Read serious books on ML engineering There's nothing called "AI in Healthcare". It's just AI, and if you know how to build and work with it, you can apply it to any field. If you're a complete beginner, this AI bundle will surely help you: https://lnkd.in/dD6kUkEA #artificialintelligence #gumroad #ai #tech #career #softwareengineering #datascience #coding #programming

OpenAI's new series of AI models is designed to spend more time thinking before they respond. They can reason through complex tasks and solve harder problems than previous models in science, coding, and math. Read for more information here https://lnkd.in/g-fk6288 #OpenAI #artificialintelligence #AI #AImodels #largelearningmodels #LLMs #technology #innovation

Just finished the learning path “Fundamentals to Become a Machine Learning Engineer”! This learning path was engaging and informational. I know a lot more about machine learning algorithms and the ways in which we can use AI to find patterns. I can't wait to learn more about machine learning! #machinelearning

Start your 2024 with these 9 Free AI courses from LinkedIn 💡 Learning AI could be the best thing you could do this year, the possibilities are endless! 1. Introduction to Prompt Engineering for Generative AI https://bit.ly/41JgVLV 2. Introduction to Artificial Intelligence https://bit.ly/47gjuWJ 3. Artificial Intelligence Foundations: Thinking Machines https://bit.ly/4aI4wvu 4. Get Ready For Generative AI https://bit.ly/4aGqIGr 5. Gpt 4 Foundations: Building AI Powered Apps https://bit.ly/47osadI 6. Prompt Engineering: How to talk to AI’s https://bit.ly/4aITxCj 7. Machine Learning with Python: Foundations https://bit.ly/41Fto2U 8. Ethics in Age of Generative AI https://bit.ly/47p5UjL 9. Hands-On AI: Build a Generative Language Model from Scratch https://bit.ly/48tmDDS ↓ Follow Utsav Soi to learn about the latest breakthroughs in AI and tech 🚀 #artificialintelligence

Thrilled to announce that: I didn’t only completeted the generative AI with LLMs course by DeepLearning.AI AI but I also built a webapp deployed with #Streamlit that allows users to query the datanerd.tech data using natural language.(An extract of it on Kaggle shout out to Luke Barousse for making it available) DATANERDTEXTSQL (webapp) https://lnkd.in/eXEh42TK Github repo: https://lnkd.in/e4jAQEg2 Learnings: Course: - Generalities of LLMs and the Transformer architecture - Prompt Engineering - Model pretraining , uses cases and project lifecycle - Fine-tuning and evaluating LLMs - Reinforcement learning with human feedback and Llm powered apps Project: - Data cleaning (how clean is clean? Tradeoff between cleanliness and information lost. Format requirements of the llms and the app dev) - Sqlite with python - Prompt engineering (any detail can change everything, few shots does not always perform better, no examples is better than bad, vague or incomplete examples,) - Secrets managenent in deployment on github and streamlit - Docker As always Krish Naik Naik the GOAT is the main from afar mentor. #generativeai #machinelearning #artificialintelligence

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