#Deep Learnings
What GPT-3 Means: GPT means generative pre-trained transformer, 3 means 3rd generation.Generative: Means bot that can generate new text.Pre-trained: Pre-trained
This document is about new way of training artificial neural network, that tries to mimic how a brain might learn.Traditional method of training AI like Back pr
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How We See Things: The Brain's Pattern Recognition Game?Have you ever looked at clouds and seen shapes in them? Or perhaps you've encountered those fascinating
Why Should You Care About CNNs?Have you ever wondered how your phone recognizes faces in photos? Or how self-driving cars can tell the difference between a pede
Power of (Python + Keras) modern deep Learning tools:This guide walks through the process of building and training an Artificial Neural Network (ANN) using Tens
Think of probability as a tool that helps us make sense of uncertainty. It's not about knowing what will happen for sure, but about understanding the chances of
Eigenvectors and Eigenvalues:we have :Now, let's say we apply linear transformation:It moves the original vector i^ to the coordinates [3, 0] & j^ to [1, 3]
Focusing on the mathematical foundations of neural network activation functions. We'll start with simple rules Transformations on functions, then explore odd, e
Tensors:Definition:A tensor is a mathematical object that describes linear relations between vectors, scalars & other tensors.They can be thought of multidi
Linear Transformation:A function that takes a vector as input and produces another vector as an output, while preserving vector addition & scalar multiplica
What's a real world application of linear algebra?Almost all of us, have used image resizing.When you resize an image on your phone, you're actually using linea
This is note is Machine Learning 101. Explanation on feature scaling. Let's see a story from a school. Imagine you're comparing different aspects of your class
Where is derivatives used in neural network?The Blue Curve (f(x)):This represents the original function, let's call it f(x).In this case, it's a parabola shape,
1. Traditional Artificial NeuronsIn all of my other notes, in all cases that i've referred to neurons. Those are traditional artificial neurons (eg: feedforward
Single layer networks vs Non-linearity:Single layer networks (perceptrons) can only solve linearly separable problems. Many real-world problem are non-linearly
What we're doing:Problem Definition:We have two binary inputs (0 or 1) and one binary output.The XOR function returns 1 if exactly one of the inputs is 1, and 0
We are going to be looking at a real example of property valuation.Takes some parameters & values the property.We have independent variables i.e 1 row of a
What is neural networks?What is Deep learning?Deep learning were invented in 1960s, it caught wind around 1980sEverybody thought that deep learning or neural ne
