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pass-the-butter
In this project we want to implement some search algorithms like: IDS, Bidirectional BFS and A*AI_Project_3
Decision_Tree_Regression_JS
mario
K-NN_JS
Support-Vector-Machine_JS
Multiple_Linear_Regression_JS
DS-in-TS
Natours-Backend
LU-Factorization
NLP_filter_toxic_comment
Toxic comments are detected and filtered using the naive Bayes classificationGenetic-algorithm
Implementation of different stages of genetic algorithmreact-project
os-final-project
Polynomial_Linear_Regression_JS
Simple_Linear_Regression_JS
Pig-Game
In this game, User Interface (UI) contains user/player that can do three things, they are as follows: Roll the dice, Hold and Resetonline-clothing-shop
Logistic_Regression_JS
Naive_Bayes_JS
js-screenshot_node-version
Modal-Window
This mini project shows how to manipulate css classes:)Random_Forest_Regression_JS
Natours-Design
monsters-rolodex
Familiarity with React basic concepts such as: class component, function component, state, props , ...Cat_vs_No-Cat
The goal is to train a classifier that the input is an image represented by a feature vector, x, and predicts whether the corresponding label y is 1 or 0. In this case, whether this is a cat image (1) or a non-cat image (0).Neural-networks-optimization-methods
Until now, I've always used Gradient Descent to update the parameters and minimize the cost. In this notebook, i will learn more advanced optimization methods that can speed up learning and perhaps even get me to a better final value for the cost function. Having a good optimization algorithm can be the difference between waiting days vs. just a few hours to get a good result.2-layer-neural-network
It's time to build my first neural network, which will have a hidden layer. You will see a big difference between this model and the one i implemented using logistic regression(cat vs not-cat)Deep_neural_network
I have previously trained a 2-layer Neural Network (with a single hidden layer). In this project, i will build a deep neural network, with as many layers as i want!Love Open Source and this site? Check out how you can help us