Hey I am on Medial • 18h
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 how they map directly to neural network units: ✓ A neuron without activation works just like a linear regression model (y = wx + b). ✔ A neuron with sigmoid activation behaves like a logistic regression model, outputting probabilities. ✔ Used TensorFlow's Keras API to build simple models, set weights manually, and visualize predictions. ✓ Understood how layers work internally and how models are initialized and used in real-world frameworks. This lab really helped me connect traditional ML concepts to how they're implemented in deep learning frameworks. #learn #machinelearning #deeplearning #tensorflow #keras #ai #neuralnetworks #regression
Hey I am on Medial • 1m
🧠 From Linear Thinking to Non-Linear Solutions: My ML Journey Just wrapped up a major milestone in my data science learning - transitioning from Logistic Regression to Support Vector Machines through Krish Naik's bootcamp. 🔍 The Learning Curve: Log
See MoreAI Deep Explorer | f... • 5m
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
See MorePassionate about tec... • 7m
Hi everyone , if you are a beginner in Data Science or wish to start , then this post is for you. Linear Regression is one of the first things you need to learn in ML. It is not just about the code . Code is not the important thing, you can make Chat
See MoreFounder Snippetz Lab... • 7m
How AI Works 1. Neural Networks – AI’s Brain AI’s neural networks consist of three layers: Input Layer: Takes in raw data (e.g., an image). Hidden Layers: Process data to find patterns (e.g., detecting edges, shapes). Output Layer: Produces the fi
See MoreJust go with the flo... • 5m
The secret to creating an error free AI is the main science behind ai is we give output and we have a expected output in between we have a fine layer in which we have neural network we need to increase the neural network in the layers instead of add
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