sitheek mohamed arsath’s Post

Demystifying Neural Networks! 🌟 Understanding neural networks is crucial for any AI/ML enthusiast. Dive into the basics of perceptrons, activation functions, and backpropagation to build a solid foundation. Whether you're a beginner or looking to brush up on your knowledge, this guide offers clear explanations and technical insights. #AI #MachineLearning #NeuralNetworks #DeepLearning #TechLearning #DataScience

AI @Dell a basic introduction to the building blocks and components of artificial intelligence, learning about concepts like algorithms, machine learning, and neural networks.

Great series on neural nets, how they learn, and even GPTs and attention. Strongly recommend for anyone interested that likes clear, math-based explanations. It helped me understand that GPTs essentially take a tokenized language, which turns the tokens/words into dimensions in a high-dimensional space (like 128,000 dimensions), and then map meaning by taking "big, juicy, hamburger", hamburger would "point" a certain direction in that space, and then be subtly rotated in space by "big" and "juicy", leaving a single vector containing all the meaning of "big, juicy, hamburger". And the "pointing" would be directionally dependent on the directions of "big" and "juicy". Link is to 1st in series, but s3e5 is the GPT one, which is great. https://lnkd.in/eb-tFKNJ

The best and the easiest-to-grasp article on how neural networks work. (Payed subscription required.) I would gladly ask the author @Shreya Rao two questions: 1) Is the same principle workable for ALL types of neural networks? 2) How does this work in LLMs? Hope, the author will answer on Medium. 🤗

Thanks for posting. More of this please. Basics people, basics

🎉 Thrilled to have earned the Machine Learning Crash Course: Neural Networks badge! Learning about the foundations of neural networks has been an exciting step in my ML journey. Looking forward to applying these insights to real-world problems! #MachineLearning #NeuralNetworks #AI #ContinuousLearning

🚀 Excited to share my latest Medium blog post: "Dropout Dramatics: Unveiling the Secret Weapon of Neural Networks"! 🧠✨ In the dynamic world of neural networks, achieving peak performance is a delicate dance between learning and adaptability. But beware the pitfalls of overfitting—where models become too rigid with their training data. Fear not! Dropout layers are here to revolutionize the game! Join me on a journey through the captivating world of dropout layers in my latest Medium blog post. 🤓💡 Discover how this ingenious technique, pioneered by Geoffrey Hinton and team, acts as the secret weapon in preventing overfitting by promoting diversity and resilience among neurons. Plus, uncover how dropout layers turbocharge training and simplify model development for us mere mortals! 🚀🧩 Whether you're a seasoned ML aficionado or an eager enthusiast, this post is your ticket to unraveling the mysteries of dropout layers and unleashing the full potential of AI. 💪🔓 Dive into the secrets of neural networks—read the full post on Medium now! 📚🔍 https://lnkd.in/gqJzeWsE #MachineLearning #NeuralNetworks #DropoutLayers #AI #TechBlog #Medium #LinkedIn

I have successfully completed a course on Attention Mechanisms in Machine Learning and Deep Learning! Understanding how models like transformers and attention-based networks can focus on the most relevant parts of the input data has been a game-changer. This powerful concept is behind so many innovations, from language models to image recognition systems. I'm thrilled to apply this knowledge to real-world problems and push the boundaries of what's possible with AI! Google Cloud Skills Boost #MachineLearning #DeepLearning #AttentionMechanism #AI #DataScience #ContinuousLearning #ProfessionalGrowth

Developed a solid understanding of deep learning fundamentals, including neural networks, backpropagation, and common architectures, such as CNNs and RNNs, for solving real-world problems.