Update repo structure

.gitignore

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+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+venv/
+
+# C extensions
+*.so
+
+# Distribution / packaging
+bin/
+build/
+develop-eggs/
+dist/
+eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+*.egg-info/
+.installed.cfg
+*.egg
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+.idea/

README.md

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+# Machine Learning from scratch
+
+## About
+This ML repository is all about coding Machine Learning algorithms from scratch by Numpy with the math under the hood without Auto-Differentiation frameworks like Tensorflow, Pytorch, etc. Some advanced models in Computer Vision, NLP require Tensorflow to quickly get the idea written in paper.
+
+## Repository structure
+As a software engineer, I follow the principle of OOP to construct the repository. You can see that `NeuralNetwork` class will use `FCLayer`, `BatchNormLayer`, `ActivationLayer` class and `CNN` class will use `ConvLayer`, `PoolingLayer`, `FCLayer`, `ActivationLayer`,... This helps me easily reuse every piece of code I wrote as well as for readable code. 
+
+## Table of contents
+- ML from scratch models:
+  * [Linear Regression](https://github.com/giangtranml/ml-from-scratch/blob/master/linear_regression/linear_regression.py)
+  * [Logistic Regression](https://github.com/giangtranml/ml-from-scratch/blob/master/logistic_regression/logistic_regression.py)
+  * [Softmax Regression](https://github.com/giangtranml/ml-from-scratch/blob/master/softmax_regression/softmax_regression.py)
+  * [Neural Network](https://github.com/giangtranml/ml-from-scratch/blob/master/neural_network/neural_network.py)
+  * [Convolutional Neural Network](https://github.com/giangtranml/ml-from-scratch/blob/master/convolutional_neural_network/convolutional_neural_network.py)
+  * [Support Vector Machine](https://github.com/giangtranml/ml-from-scratch/blob/master/svm/svm.py)
+
+- Deep Learning layers:
+  * [Fully-Connected Layer](https://github.com/giangtranml/ml-from-scratch/blob/master/nn_components/layers.py#L43)
+  * [Convolutional Layer](https://github.com/giangtranml/ml-from-scratch/blob/master/nn_components/layers.py#L107)
+  * [Pooling Layer](https://github.com/giangtranml/ml-from-scratch/blob/master/nn_components/layers.py#L245)
+  * [Activation Layer](https://github.com/giangtranml/ml-from-scratch/blob/master/nn_components/layers.py#L372)
+  * [BatchNorm Layer](https://github.com/giangtranml/ml-from-scratch/blob/master/nn_components/layers.py#L436)
+  * [Dropout Layer](https://github.com/giangtranml/ml-from-scratch/blob/master/nn_components/layers.py#L407)
+
+- Optimization algorithms:
+  * [SGD](https://github.com/giangtranml/ml-from-scratch/blob/master/optimizations_algorithms/optimizers.py#L16)
+  * [SGD with Momentum](https://github.com/giangtranml/ml-from-scratch/blob/master/optimizations_algorithms/optimizers.py#L24)
+  * [RMSProp](https://github.com/giangtranml/ml-from-scratch/blob/master/optimizations_algorithms/optimizers.py#L37)
+  * [Adam](https://github.com/giangtranml/ml-from-scratch/blob/master/optimizations_algorithms/optimizers.py#L51)
+
+- Advanced models:
+  * [Bahdanau Attention Mechanism](https://github.com/giangtranml/ml-from-scratch/blob/master/attention_mechanism/Bahdanau%20Attention%20Mechanism.ipynb) 
+  * [Luong Attention Mechanism](https://github.com/giangtranml/ml-from-scratch/blob/master/attention_mechanism/Luong%20Attention%20Mechanism.ipynb)
+  * [Transformer](https://github.com/giangtranml/ml-from-scratch/blob/master/transformer/Transformer.ipynb)