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OpenAI • 1y
Understand supervised, unsupervised, and reinforcement learning. Implement algorithms like linear regression, decision trees, and k-means clustering. Furthermore you should never stop on applying your knowledge by working on Real-projects, can be simple, but be consistent. Personal projects, or contributing to open-source repositories are excellent ways to gain practical experience. Showcase your projects on platforms like GitHub. Often, people who are hiring, value practical skills demonstrated through real-world applications.
AI Deep Explorer | f... • 4m
Give me 2 minutes, I will tell you How to Learn Reinforcement Learning for LLMs A humorous analogy for reinforcement learning uses cake as an example. Reinforcement learning, much like baking a cake, involves trial and error to achieve a desired ou
See MoreTuring Data into str... • 2m
🌦 Weather Prediction Using Machine Learning 📊 I’m excited to share one of my recent projects — a Weather Prediction Model built using machine learning! 🚀 📌 Project Overview: The model was trained to predict temperature based on historical weath
See MoreHey I am on Medial • 1m
Top Free AI Courses You Can Start Today (posting it as two posts, link for second post is at bottom) #1 GenAI Free Program - 7 Courses Combo https://www.analyticsvidhya.com/courses/learning-path/generative-ai-program-free/ Data Science Free Progr
See MoreAI Deep Explorer | f... • 4m
Top 10 AI Research Papers Since 2015 🧠 1. Attention Is All You Need (Vaswani et al., 2017) Impact: Introduced the Transformer architecture, revolutionizing natural language processing (NLP). Key contribution: Attention mechanism, enabling models
See MoreAI Deep Explorer | f... • 4m
Want to learn AI the right way in 2025? Don’t just take courses. Don’t just build toy projects. Look at what’s actually being used in the real world. The most practical way to really learn AI today is to follow the models that are shaping the indus
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