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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

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.

Imagine a world where your entire dev stack is open-source, community-driven, and optimized for performance — that’s ProXentix. Whether you're working on websites, mobile apps, or data science, we provide frameworks that are easy to learn and powerfu

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

🚀 Looking for a Co-Founder – AI Engineer 🤖 We’re building Fluency AI, an AI-powered language learning app that helps users learn through real conversations. Our team is growing, and we’re looking for a co-founder with AI expertise to help bring th

Python + AI Entrepreneurship Roadmap Stage 1 – Identify AI Opportunity (Solve Real-World Problems) Stage 2 – Build Python/AI Skills (ML, Deep Learning) Stage 3 – Design AI Product (Prototyping with Flask/TensorFlow) Stage 4 – Validate AI Model (Data

Dive into the world of innovation with OpenAl! From groundbreaking technology to ethical Al development, key partnerships, and a vision for the future, OpenAl is shaping tomorrow's world today.

7 Podcasts to Supercharge Your Machine Learning Knowledge 1. The AI Podcast (NVIDIA) Dive into real-world AI applications with expert insights from NVIDIA. 2. TWIML AI Podcast (TWIML) Stay ahead of the curve with deep learning trends and exper

AI Resources for Beginners Books: 1. Deep Learning. Illustrated Edition. Ian Goodfellow, Yoshua Bengio, and Aaron Courville. 2. Mathematics for Machine Learning. Deisenroth, A. Aldo Faisal, and Cheng Soon Ong. 3. Reinforcement learning, An Introd

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