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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
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Just completed a deep dive into how neurons and layers in neural networks mirror linear and logistic regression and how TensorFlow simply automates the math we've already learned. I revisited core concepts from linear and logistic regression and saw
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CompSciย โขย 1y
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.
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Imagine a world where your entire dev stack is open-source, community-driven, and optimized for performance โ thatโs ProXentix. Whether you're working on websites, mobile apps, or data science, we provide frameworks that are easy to learn and powerfu
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Day 2/100 : free AI resources sharing topic of day : machine learning Books โMachine Learning For Absolute Beginnersย by Oliver Theobald https://mrce.in/ebooks/Machine%20Learning%20for%20Absolute%20Beginners.pdf โHands-On Machine Learning with
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๐ Looking for a Co-Founder โ AI Engineer ๐ค Weโre building Fluency AI, an AI-powered language learning app that helps users learn through real conversations. Our team is growing, and weโre looking for a co-founder with AI expertise to help bring th
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Vibe Coding: The Future of Software Development?? A Deep Dive into Vibe Coding: Best Tools, Real-World Examples, and How This AI-Driven Approach Is Shaping the Future of App Development. Read Full article: https://career-tech-insight.beehiiv.com/p/
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๐ง *Technologies for Data Science, Machine Learning & AI!* part 1 ๐ *Data Science* โช๏ธ Python โ The go-to language for Data Science โช๏ธ R โ Statistical Computing and Graphics โช๏ธ Pandas โ Data Manipulation & Analysis โช๏ธ NumPy โ Numerical Computing โช๏ธ
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Python + AI Entrepreneurship Roadmap Stage 1 โ Identify AI Opportunity (Solve Real-World Problems) Stage 2 โ Build Python/AI Skills (ML, Deep Learning) Stage 3 โ Design AI Product (Prototyping with Flask/TensorFlow) Stage 4 โ Validate AI Model (Data
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