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26 search results found

Tensorflow_cookbook ⭐ 6,085

Code for Tensorflow Machine Learning Cookbook

Kmeans_pytorch ⭐ 193

kmeans using PyTorch

The Deep Learning With Keras Workshop ⭐ 40

An Interactive Approach to Understanding Deep Learning with Keras

Music Clustering ⭐ 35

K-Means Clustering and PCA to categorize music by similar audio features

Kmeans_elbow ⭐ 35

Code for determining optimal number of clusters for K-means algorithm using the 'elbow criterion'

Machinelearningseries ⭐ 28

Vídeos e códigos do Universo Discreto ensinando o fundamental de Machine Learning em Python. Para mais detalhes, acompanhar a playlist listada.

Stock Market Analysis ⭐ 27

Exploratory analysis, visualization of stock market data along with predictions made on it using different techniques.

Tensorbag ⭐ 24

Collection of tensorflow notebooks tutorials for implementing the most important Deep Learning algorithms.

Study Of David Mackay S Book ⭐ 21

David Mackay's book review and problem solvings and own python codes, mathematica files

Hyperbolic Learning ⭐ 18

Implemented ML algorithms in hyperbolic geometry (MDS, K-Means, Support vector machines, etc.)

Coursera Deeplearning.ai Stanford University Machine Learning Specialization ⭐ 18

This Repository contains Solutions to the Quizes & Lab Assignments of the Machine Learning Specialization (2022) from Deeplearning.AI on Coursera taught by Andrew Ng, Eddy Shyu, Aarti Bagul, Geoff Ladwig.

Clustering In Python ⭐ 17

Clustering methods in Machine Learning includes both theory and python code of each algorithm. Algorithms include K Mean, K Mode, Hierarchical, DB Scan and Gaussian Mixture Model GMM. Interview questions on clustering are also added in the end.

Ml_from_scratch ⭐ 16

Implementation of basic ML algorithms from scratch in python...

Amazon Fine Food Review ⭐ 16

Machine learning algorithm such as KNN,Naive Bayes,Logistic Regression,SVM,Decision Trees,Random Forest,k means and Truncated SVD on amazon fine food review

🐍 Data Science Boot-Camp : UC San DiegoX

Clustering_analysis ⭐ 12

Performs an exploratory analysis on a dataset containing information about shop customers. Check that the assumptions K-means makes are fulfilled. Apply K-means clustering algorithm in order to segment customers.

Tsp Essay ⭐ 12

A fun study of some heuristics for the Travelling Salesman Problem.

Machine Learning From Scratch ⭐ 12

🤖 Python implementations of some of the fundamental Machine Learning models and algorithms from scratch with interactive Jupyter demos and math being explained.

Dataquest ⭐ 12

Data Science Massive Open Online Course: All the code, notes and supplementary materials generated during the course of my data scientific learning.

Energy Consumption Clustering ⭐ 11

Discovering energy consumption patterns of residential and commercial users.

Dsu_insure_sp19_ids_prioritization ⭐ 10

IDS Alert Prioritization INSuRE Research Project

Credit Card Fraud Detection ⭐ 10

The notebook contains Python code for various machine learning tasks and models. Here is an overview of its content:

Grocery_recommendation ⭐ 10

Grocery Recommendation on Instacart Data

K Means U Star ⭐ 10

implementation of the k-means-u* clustering algorithm

Country Profiling Using Pca And Clustering ⭐ 9

Unsupervised Machine Learning Analysis Using Clustering Model

The Machine Learning Workshop ⭐ 9

An interactive approach to understanding Machine Learning using scikit-learn

Machine_learning ⭐ 8

Best collection of machine learning & deep learning algorithms implemented from scratch using python.

Customer Segmentation Using Clustering Algorithms ⭐ 8

Customer Segmentation Using Unsupervised Machine Learning Algorithms

Study 09 Machinelearning E ⭐ 8

**Unsupervised-Learning**(with practice of PCA, ICA and Model-based Clustering)

Clustering Based Anomaly Detection ⭐ 8

This clustering based anomaly detection project implements unsupervised clustering algorithms on the NSL-KDD and IDS 2017 datasets

Data Science Portfolio ⭐ 7

Data Science Portfolio created for academic and personal projects.

Esg_clustering ⭐ 7

A tool to cluster ESG stocks and cryptocurrency by return data to identify similar assets with higher ESG scores.

K_means_iris_dataset ⭐ 7

KMeans Clustering for IRIS Dataset Classification

Centroid Neural Networks ⭐ 7

Centroid Neural Network for Unsupervised Competitive Learning

Clustering Of Mall Customers ⭐ 6

Clustering Analysis Performed on the Customers of a Mall based on some common attributes such as salary, buying habits, age and purchasing power etc, using Machine Learning Algorithms.

Market Segmentation In Sbi Life Insurance ⭐ 6

A machine learning clustering model for customer segmentation to define marketing strategy.

K Means_customer_segmentation ⭐ 6

Using K-Means algorithm for customer segmentation due to credit card behavior

Unsupervised Features Learning For Image Classification ⭐ 6

Recently, image classification draw attentions of many researchers. The need of object recognition grows drastically, especially in the context of biometric, biomedical imaging and real time scene understanding. Computer vision task is the most challenging in machine learning. For that reason, it's fundamental to tackle this concern using appropriate clustering and classification techniques. However, the quest for the best unsupervised features extraction remain an open problem even if CNNs r

Handbook For Business Growth ⭐ 6

Data driven growth

Clarusway_machine_learning_course ⭐ 6

This repository contains the Machine Learning lessons I took from the Clarusway Bootcamp between 10 Aug - 14 Sep 2022 and includes 17 sessions, 5 labs, 4 case studies, 5 weekly agendas, and 3 projects.

Ml Algorithms Collection ⭐ 5

Machine Learning Practice ⭐ 5

Repository containing introduction to scikit-learn to provide hands-on problem solving experience for all the methods and models learnt in MLT.

Yonsei Exchange Program ⭐ 5

✈️ Analyzing Student Exchange Program with NLP

Kaggle_kernels ⭐ 5

It's contain a Data scince - Machine learning ,Data visualizations codes & Datasets

Predicting Power Output Of A Combined Cycle Power Plant. ⭐ 5

The objective of the Project is to predict ‘Full Load Electrical Power Output’ of a Base load operated combined cycle power plant using Polynomial Multiple Regression. Concepts : 1) Clustering, 2) Polynomial Regression, 3) LASSO, 4) Cross-Validation, 5) Bootstrapping

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