AIND Jupyter Notebook to predict student admissions using Keras Neural Networks
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Updated
Jun 19, 2017 - Jupyter Notebook
AIND Jupyter Notebook to predict student admissions using Keras Neural Networks
Introductory level artificial neural network
Artificial Intelligence using the sigmoid function.
creating a binary classifier that is capable of predicting whether applicants will come out successful after receiving funding by an investor.
Advance Machine Learning (CSL 712) Course Lab Assignments
A implementation of a Neural Network in vanilla python that trains on the MNIST handwritten digit classifiction problem.
Mini-learn is a miniature version of tensor-flow which I made with ONLY NUMPY to play with perceptrons. You can use this project like you use tflearn. Go to https://github.com/Satyaki0924/boston-housing-with-minilearn to see it's usage.
Fortran backward (reverse) mode automatic differentiation.
TensorFlow 2.2, Keras, Deep Learning
This repo is created for learning about computer vision and pattern recognition
Deep Learning
Standard logistic function.
Logit function.
This is an ongoing project intended to make it easier to use neural network creation, genetic algorithms, and other data science and machine learning skills.
Using the features in the provided dataset, creating a binary classifier that can predict whether applicants will be successful if funded by Alphabet Soup.
Artificial Natural Network Perceptron (Forward Pass and Back Propagation). Weights and Bias. Forward Pass: Net Input Function, Activation Function (Sigmoid). Threshold. Back Propagation: Binary Cross Entropy Loss, Computing Gradients/ Slopes/ Derivatives, Gradient Descent Step, Epoch.
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