ahmedbesbes/Neural-Network-from-scratch

Ever wondered how to code your Neural Network using NumPy, with no frameworks involved?

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je-suis-tm/machine-learning

Python machine learning applications in image processing, recommender system, matrix completion, netflix problem and algorithm implementations including Co-clustering, Funk SVD, SVD++, Non-negative Matrix Factorization, Koren Neighborhood Model, Koren Integrated Model, Dawid-Skene, Platt-Burges, Expectation Maximization, Factor Analysis, ISTA, FISTA, ADMM, Gaussian Mixture Model, OPTICS, DBSCAN, Random Forest, Decision Tree, Support Vector Machine, Independent Component Analysis, Latent Semantic Indexing, Principal Component Analysis, Singular Value Decomposition, K Nearest Neighbors, K Means, Naïve Bayes Mixture Model, Gaussian Discriminant Analysis, Newton Method, Coordinate Descent, Gradient Descent, Elastic Net Regression, Ridge Regression, Lasso Regression, Least Squares, Logistic Regression, Linear Regression

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gyrdym/ml_algo

Machine learning algorithms in Dart programming language

Language: Dart - Size: 9.49 MB - Last synced at: 21 days ago - Pushed at: 21 days ago - Stars: 192 - Forks: 31

IvanBongiorni/TensorFlow2.0_Notebooks

Implementation of a series of Neural Network architectures in TensorFow 2.0

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harshraj11584/Paper-Implementation-Overview-Gradient-Descent-Optimization-Sebastian-Ruder

[Python] [arXiv/cs] Paper "An Overview of Gradient Descent Optimization Algorithms" by Sebastian Ruder

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bhattbhavesh91/gradient-descent-variants

My implementation of Batch, Stochastic & Mini-Batch Gradient Descent Algorithm using Python

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tazriahelal/Gradient-Descent

Gradient Descent(From Scratch & With TensorFlow)

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burhanahmed1/TwitSpark

Advanced Twitter sentiment analysis pipeline using Apache Spark for distributed data processing, featuring TF-IDF–based feature engineering and stochastic gradient-descent classification for scalable, real-time sentiment insights.

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longtng/Stochastic-Gradient-Descent

The laboratory from CLOUDS Course at EURECOM

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DeepraMazumder/Social-Network-Ads-Prediction-Analysis

A Machine Learning project to predict user interactions with social network ads using demographic data to optimize ad targeting

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Abdelrahman13-coder/Optimization

This repository includes implementation of the basic optimization algorithms (Batch-Mini-stochatic)Gradient descents and NAG,Adagrad,RMSProp and Adam)

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hager51/Numerical-Optimization

Numerical Optimization for Machine Learning & Data Science

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tate8/softmax-regression

Softmax Regression from scratch. MNIST dataset

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Vedant2311/Machine-Learning-Algorithms

Compilation of different ML algorithms implemented from scratch (and optimized extensively) for the courses COL774: Machine Learning (Spring 2020) & COL772: Natural Language Processing (Fall 2020)

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pwc2/ridge-regression

Implementation of linear regression with L2 regularization (ridge regression) using numpy.

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prabhuvashwin/Credit-Card-Fraud-Detection 📦

Naive Bayes classifier and Logistic Regression classifier to predict whether a transaction is fraudulent or not

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YousefAlaaAli/Gradient-descent

A practical comparison of gradient descent algorithms to predict student performance using study and lifestyle data, with visual analysis.

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Khushi130404/Gradient_Realm

Gradient_Realm is a Python project exploring regression techniques and optimization methods like Regularization, Batch, Stochastic, and Mini-batch Gradient Descent. It uses scikit-learn and custom implementations for hands-on learning.

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AmbreenMahhoor/What-Is-Gradient-Descent-And-Its-Variants

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NILAY2233/Machine_Learning--Learning-Gradient-Descent-optimization-technique

Gradient Descent is a technique used to fine-tune machine learning algorithms with differentiable loss functions. It's an open-ended mathematical expression, tirelessly calculating the first-order derivative of a loss function and making precise parameter adjustments.

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NILAY2233/Machine_Learning---Learning-Gradient-Descent-optimization-techniques

Gradient Descent is a technique used to fine-tune machine learning algorithms with differentiable loss functions. It's an open-ended mathematical expression, tirelessly calculating the first-order derivative of a loss function and making precise parameter adjustments.

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GellertPalfi/CS229-ML-algorithms-from-scratch

Following and implementing (some of) the machine learning algorithms from scratch based on the Stanford CS229 course.

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shimazadeh/Ft_logistic_regression

Recreated Poudlard's Sorting Hat by implementing logistic regression from scratch.

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ChaitanyaK77/SGD-v-s-BGD

Implementation and in-depth comparative analysis of two foundational machine learning optimization algorithms, Stochastic Gradient Descent (SGD) and Batch Gradient Descent (BGD).

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bharghavs/House-Price-Prediction---Linear-Regression

Linear Regression - Batch Gradient Descent

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thinhnguyen0311/Gradient-Descent-Implementation

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MinhQuan-Github/Gradient-Descent

Gradient Descent with multiple method: Univariate - Multivariate, Momentum, Batch Gradient Descent, ...

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AshiniAnantharaman/NeuralNetwork

Has the basics of Neural network like Activation, loss and gradient descent functions.

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MahsaAm2/insurance-dataset

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afnanAlgogandi/TEMPERATURE-PREDICTION

developed a model that can predict air temperature according to atmospheric pressure.

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chrisse22222/AI_Course

Assignments from the AI course.

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eskinderit/SGD

An easy implementation of the Stochastic / Batch gradient descent and comparison with the standard Gradient Descent Method

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vitthal-bhandari/High-Dimensional-Data-and-Gradient-Descent

Analyzing and overcoming the curse of dimensionality and exploring various gradient descent techniques with implementations in R

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mvrck96/Coursework--Optimisation

Coursework on global optimization methods (BGD, Adadelta)

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alexaapo/Linear-Regression

Implement Linear Regression class and experiment with Batch, Mini Batch and Stohastic Gradient Descent

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spyros-briakos/Linear_Regression

Implement Linear_Regression class and experiment with Batch,Mini Batch and Stohastic Gradient Descent!

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cryptomanic/DeepLearningBasics

Just exploring Deep Learning

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kirushyk/le-board

Debugging tool for Le Framework

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sdevalapurkar/linear-regression-models

⚛️ Experimenting with three different algorithms to train linear regression models

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akshaykulkarni07/deep_learning_models

Use of various deep learning models to classify flowers. Models are implemented from scratch in PyTorch using only tensor operations.

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anuragkumar/Gradient-Descent-for-Squared-Loss

Batch Gradient Descent for Supervised Machine Learning

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devonlee111/Basic-Neural-Net

A basic neural net built from scratch.

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hademircii/Ham-Spam-Detector

Detect Spam E-Mails

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