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Machine learning algorithms implemented from scratch.

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.ipynb_checkpoints
.ipynb_checkpoints
 
 
Test Data TSP
Test Data TSP
 
 
Testing Data
Testing Data
 
 
boards
boards
 
 
datasets
datasets
 
 
nonograms
nonograms
 
 
plots
plots
 
 
rushhour
rushhour
 
 
solutions_ga
solutions_ga
 
 
.gitignore
.gitignore
 
 
CSP solver.ipynb
CSP solver.ipynb
 
 
Interface to tensorflow.ipynb
Interface to tensorflow.ipynb
 
 
Linear and Logistic Regression.ipynb
Linear and Logistic Regression.ipynb
 
 
Linear and Logistic Regression.py
Linear and Logistic Regression.py
 
 
None0000000.png
None0000000.png
 
 
Project1 AI Programming.py
Project1 AI Programming.py
 
 
README.md
README.md
 
 
SOM MNIST.ipynb
SOM MNIST.ipynb
 
 
SOM TSP.ipynb
SOM TSP.ipynb
 
 
Search.ipynb
Search.ipynb
 
 
Untitled.py
Untitled.py
 
 
Untitled.txt
Untitled.txt
 
 
__init__.py
__init__.py
 
 
ga_demo.ipynb
ga_demo.ipynb
 
 
ga_demo.py
ga_demo.py
 
 
genetic_algorithm.py
genetic_algorithm.py
 
 
mnist_x.npy
mnist_x.npy
 
 
mnist_y.npy
mnist_y.npy
 
 
opt.py
opt.py
 
 
pima-indians-diabetes.names
pima-indians-diabetes.names
 
 
tflowtools.py
tflowtools.py
 
 

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AI and Machine learning algorithms from scratch

This repository will contain a wide selection of AI and ML algorithms in the form of Jupyter Notebooks. Many of the implementations are done as part of University Course or MOOC assignments.

  1. Linear and logistic regression
  2. Search
  3. Constraint Satisfaction Problem Solving
  4. An interface to tensorflow
  5. Self Organizing Map for Unsupervised Learning of MNIST
  6. Self Organizing Map for solving Travelling Salesperson Problem
  7. Genetic algorithm for solving Multi-Depot Vehicle Routing Problem

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Machine learning algorithms implemented from scratch.

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