This repository summarizes the basic concepts, types and usage scenarios of activation functions in deep learning.
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Updated
Aug 12, 2022
This repository summarizes the basic concepts, types and usage scenarios of activation functions in deep learning.
Push features to OSM taked from satellite images.
Practice of implementing Multilayer Perceptron trained with Stochastic Gradient Descent for Seoul AI Meetup on June 25, 2017.
This is the code for "sigmoid binary classification without using and ML library" By M.Junaid Fiaz
This course will take a look at autoencoders and their applications will help you see how autoencoders are used in dimensionality reduction and denoising. You will implement an artificial neural network and an autoencoder using the Keras framework. By the end of this course, you will be able to implement an autoencoder model using convolutional …
utility notebooks
A Mathematical Intuition behind Logistic Regression Algorithm
I have implemented some AI projects from scratch implementation without explicit use of the built-in-libraries and thus added to this repo.
Predict whether the cancer is benign or malignant using logistic regression model.
2nd Project of Course 'Machine Learning' of the SMARTNET programme. Taken at the National and Kapodistrian University of Athens.
Implementation Neural Network in C++
Basic level implementation of Neural Network
Pyhton projects on various topics
SVMs are used for Classification as well as Regression problems. However, it is primarily used for Classification problems. #%% md # The Technique (Support Vector Machine) Support Vector Machine or SVM is one of the most popular Supervised Learning algorithms, which is used for Classification as well as Regression problems. However, primarily, i…
This project provided practice with logistic regression and the cost functions MSE and log loss
A simple, single-layer, neural network
Deep Learning with TensorFlow Keras and PyTorch
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