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Here are some AI tools which are useful for the startups: 1. TensorFlow and PyTorch: Open-source frameworks for building machine learning models. 2. IBM Watson: Offers AI tools and services like natural language understanding and computer vision.

Tools for developers: Unleash Machine Learning with Colab (Free!) Google Colab lets you explore machine learning without needing a fancy computer. It's free, cloud-based, and runs on powerful servers. Train complex models and analyze massive data

Day 2/100 : free AI resources sharing topic of day : machine learning Books ✓Machine Learning For Absolute Beginners by Oliver Theobald https://mrce.in/ebooks/Machine%20Learning%20for%20Absolute%20Beginners.pdf ✓Hands-On Machine Learning with

Excited to dive into Hands-on Machine Learning with Scikit-Learn, Keras & TensorFlow Machine learning is evolving rapidly, and this book is a goldmine for anyone looking to build intelligent systems using the latest tools and frameworks. From Scikit

this is why open source wins. closed models are only gonna get more restrictive over time.

Best Open Source LLM:Tencent Hunyuan-Large: The 389 Billion Parameter Model Outperforming Llama 3 and DeepSeek V2

Meta, formerly Facebook, has unveiled two new open-source AI models called Llama 3 8B and Llama 3 70B, with 8 billion and 70 billion parameters respectively. 🚀 These models outperform some rivals and spark debate over open versus closed source AI de

Will AI hit a wall? 🤔 Future advanced models need complex data—but is there enough available? Or are we running out of high-quality training data? What’s the solution? More synthetic data? Better datasets? Discuss! ⬇️

Bhavish Aggarwal’s AI startup, Krutrim AI, has begun hosting Chinese GenAI company DeepSeek’s open-source models on its cloud platform. Five models, ranging from 8 billion to 70 billion tokens, are now live on Indian servers at the world’s lowest p

Tech giants like Google, Microsoft, Amazon, and Facebook are major contributors to open source projects such as Kubernetes, React, and TensorFlow. Their involvement provides resources, governance, and wider adoption but raises concerns about control