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Hetansh Modh

Hey I am on Medial • 2m

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

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Inayat Hasan

Software engineer • 1y

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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

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Ayush gandewar

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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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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