Deep-Learning-Notes

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Deep-Learning-Notes

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This repo contains detail deep learning Notes.

Deep-Learning-Notes 최신버젼 다운로드

최종 버전 다운로드 (.zip)

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# Deep-Learning Notes

![Deep_Learning](https://github.com/sachinkumar1609/100-Days-of-Deep-Learning/assets/103982094/95c96cc9-f324-4cea-93b0-fd165c1f5f83)

|Daywise| Blog |
|-|-|
|Day1 ( Machine Learning vs Deep Learning )| [Explanation Link](https://x.com/Sachintukumar/status/1755284231515967579?s=20)
|Day2 ( Types of Neural Network  )| [Explanation Link](https://x.com/Sachintukumar/status/1755659435073302958?s=20)
|Day3 ( What is Perceptron & Perceptron vs Neuron )| [Explanation Link](https://x.com/Sachintukumar/status/1756340578697281716?s=20) 
|Day4 ( Perceptron Trick )| [Explanation Link](https://x.com/Sachintukumar/status/1756649343933911406?s=20) 
|Day5 ( Perceptron Loss Function & It's Limitation )| [Explanation Link](https://x.com/Sachintukumar/status/1758208993372356994?s=20) 
|Day6 ( Multilayer Perceptrons  )| [Explanation Link](https://x.com/Sachintukumar/status/1758734882896068729?s=20)
|Day7 ( Forward Propagation )| [Explanation Link](https://x.com/Sachintukumar/status/1758897570263470362?s=20)
|Day8 ( Customer Churn #Prediction Using ANN )| [Explanation Link](https://x.com/Sachintukumar/status/1759636609543381132?s=20)
|Day9 ( Handwritten-Digit-Classification using ANN  )| [Explanation Link](https://x.com/Sachintukumar/status/1760002907221655872?s=20)
|Day10 ( Admission Prediction using ANN  )| [Explanation Link](https://x.com/Sachintukumar/status/1760350716898812318?s=20)
|Day11 ( Loss Function   )| [Explanation Link](https://x.com/Sachintukumar/status/1760715405730173270?s=20)
|Day12 ( BackPropagation   )| [Explanation Link](https://x.com/Sachintukumar/status/1762894827195392087?s=20)
|Day13 ( Multilayer Perceptron Memoization   )| [Explanation Link](https://x.com/Sachintukumar/status/1763253513835221425?s=20)
|Day14 (  Gradient Descent & Vectorization  )| [Explanation Link](https://x.com/Sachintukumar/status/1763897818257985934?s=20)
|Day15 ( Vanishing & Exploding Gradient Problem )| [Explanation Link](https://x.com/Sachintukumar/status/1764182164504187117?s=20)
|Day16 ( Early Stopping in Neural Network )| [Explanation Link](https://x.com/Sachintukumar/status/1764678995361268047?s=20)
|Day17 ( Data Scaling in Neural Network )| [Explanation Link](https://x.com/Sachintukumar/status/1765066624820977951?s=20)
|Day18 ( Dropout Layer 🧬  )| [Explanation Link](https://x.com/Sachintukumar/status/1765428888128344472?s=20)
|Day19 ( Regularization  )| [Explanation Link](https://x.com/Sachintukumar/status/1765767487768150294?s=20)
|Day20 ( Activation Function )| [Explanation Link](https://x.com/Sachintukumar/status/1766513253918683477?s=20)
|Day21 ( Weight Initialization )| [Explanation Link](https://x.com/Sachintukumar/status/1767246123515969981?s=20)
|Day23 ( Optimizer 🎚️ )| [Explanation Link](https://x.com/Sachintukumar/status/1767961775386005635?s=20)
|Day24 ( Exponentially Weighted Moving Average EWMA )| [Explanation Link](https://x.com/Sachintukumar/status/1768682747026145650?s=20)
|Day25 ( Stochastic Gradient Descent (SGD) with Momentum )| [Explanation Link](https://x.com/Sachintukumar/status/1769040008529490201?s=20)
|Day26 ( Nesterov Accelerated Gradient (NAG) Optimizer )| [Explanation Link](https://x.com/Sachintukumar/status/1769324295313109370?s=20)
|Day27 ( AdaGrad Optimization )| [Explanation Link](https://x.com/Sachintukumar/status/1769695137934774474?s=20)
|Day28 ( RMSProp Optimizer & Adam Optimizer )| [Explanation Link](https://x.com/Sachintukumar/status/1770144746846949665?s=20)
|Day29 (  Keras Tuner & Hyperparameter Tuning )| [Explanation Link](https://x.com/Sachintukumar/status/1770495690256306433?s=20)
|Day30 ( Convolutional Neural Network )| [Explanation Link](https://x.com/Sachintukumar/status/1770868261808140467?s=20)
|Day31 ( Convolution Operation  )| [Explanation Link](https://x.com/Sachintukumar/status/1771442217015443555?s=20)
|Day32 ( Padding & Strides  )| [Explanation Link](https://x.com/Sachintukumar/status/1771806525448708534?s=20)
|Day33 ( Pooling Layer  )| [Explanation Link](https://x.com/Sachintukumar/status/1772270086495092896?s=20)
|Day34 ( CNN Architecture & CNN vs ANN  )| [Explanation Link](https://x.com/Sachintukumar/status/1772657013597651050?s=20)
|Day35 ( Backpropagation in CNN  )| [Explanation Link](https://x.com/Sachintukumar/status/1773038218625077372?s=20)
|Day36 ( Data Augmentation  )| [Explanation Link](https://x.com/Sachintukumar/status/1773962109958705224?s=20)
|Day37 ( Pre-trained Model in CNN )| [Explanation Link](https://x.com/Sachintukumar/status/1807015338912973077)
|Day38 ( Visualize Filters and Feature Maps in CNN )| [Explanation Link](https://x.com/Sachintukumar/status/1807445892003209444)
|Day39 ( Transfer Learning )| [Explanation Link](https://x.com/Sachintukumar/status/1808932587399684147)
|Day 40 ( Keras Functional Model )| [Explanation Link](https://x.com/Sachintukumar/status/1809571942548013517)
|Day 41 ( Recurrent Neural Network (RNN) )| [Explanation Link](https://x.com/Sachintukumar/status/1810370725561381177)
|Day 42 ( RNN Architecture & Forward Propagation )| [Explanation Link](https://x.com/Sachintukumar/status/1813253041262620897)
|Day 43 ( Backpropagation in RNN & Problems with RNN )| [Explanation Link](https://x.com/Sachintukumar/status/1815008274757931218)
|Day 44 ( Understanding LSTM Networks )| [Explanation Link](https://x.com/Sachintukumar/status/1824084455293902897)
|Day 45 ( Gated Recurrent Unit (GRU) )| [Explanation Link](https://x.com/Sachintukumar/status/1833162505142595626)
|Day 46 ( Deep Recurrent Neural Network (Deep RNN) )| [Explanation Link](https://x.com/Sachintukumar/status/1837498983922475362)
|Day 47 ( BiDirectional RNN (Bi-RNNs)) | [Explanation Link](https://x.com/Sachintukumar/status/1839639446771105890)
|Day 48 ( The Epic History of #LLMs : Journey from RNNs to ChatGPT )) | [Explanation Link](https://x.com/Sachintukumar/status/1840398980053651822)
|Day 49 ( Encoder Decoder & Sequence-to-Sequence Architecture )) | [Explanation Link](https://x.com/Sachintukumar/status/1871166199335383155)

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