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an implementation of a Radial Basis Function Neural Network (RBFNN) for classification problem.
Diseases Prediction System though Machine Learning with code and documents
End to end implementation and deployment of Machine Learning Car Price Prediction using python, flask, gunicorn, scikit-Learn, etc. on Heroku web application platform.
Implementation & Learning of Compression of Image through use of K-means Clustering Algorithm
Implements a genetic algorithm to select the most impactful features in a dataset to improve classifier performance. Written in Jupyter Notebook using pandas, numpy, scikit-learn. Results displayed with accuracy, precision, recall, F1 score comparison to using all features.
Machine Learning model development for a transport company, the objective is to predict whether an order will arrive on time or not.
Classifier des mails avec des outils ML
First exercise on simple linear regression and working with numpy and scikit-learn
Trying to use power of machine learning to predict stock prices
PSO feature selection improves classifier performance. Implemented in Jupyter Notebook with pandas, numpy, scikit-learn. PSO done from scratch. Results compared using accuracy, precision, recall, F1 score. Improves results compared to using all features. Can be applied to various classification problems.
Sentiment Analysis Using Bert Transformer
We solve a regression problem in which it consists of calculating the health insurance charge in the United States Where we will break down the project into 5 phases: Exploratory Analysis. Feature Engineering. Selection of the ideal model. Development of the final model. Creation of a web application in streamlit.
PySpark Python ML Models
NLP repository with projects like Article Classifiers, Recommender Systems and Text Processing
A Website powered by Machine Learning to find the shortest and safest route dynamically, based on traffic changes for Delhi Metro Services.
The objective of this challenge is to accurately predict the soil moisture level multiple days in advance. This solution will help farmers prepare their irrigation schedules more efficiently
Image Processing Grades Auto filler with 2 models Graded Sheet Model & Bubble Sheet Model
KNN and Decision Tree
Own Course for Udemy. In progress: Daily Projects for convert in Professional Python Developer.
a maching learning model to automating the detection of spam in emails
Novel-Corona Virus or Covid-19 :Visualisation,Forecasting ,Analysis,Maps,Bar Race Charts,Starter Codes,Modelling,Forecasting,Estimation
EDA and Feature engineering with Plotly library!
A task of sentiment analysis. Classify the Bengali book reviews into positive and negative sentiment.
Este proyecto ha sido desarrollado utilizando modelos de ML ππ con el fin de predecir el rendimiento del arΓ‘ndano silvestre π± .
Implementation & Learning of Iris Data-set and use of various Machine learning Algorithm
Distributed System Fault Diagnosis System based on Machine Learning
This project aims to develop a machine learning model using Logistic Regression for classifying loan credit applications as either approved or rejected.
Coronary heart disease analysis, dataset - https://www.kaggle.com/datasets/billbasener/coronary-heart-disease. For analysis i used: k-means clustering, k-neighbors classifier, decision tree classifier. Libraries: scikit-learn.
Estudos MachineLearning/DataScience/IA... πΈπππ¨π§π·
A collection of machine learning models for predicting laptop prices
Data-oriented Python course taught for all Mercado Libre verticals
Sample codes in Python of machine learning models for enterprise financial applications using scikit-learn and PyTorch
π‘οΈ Spam classifier using Python, capable of accurately categorizing messages as spam or non-spam. Leveraging machine learning techniques and natural language processing, it's a robust tool for filtering unwanted messages.
A recommendation system created for H&M created with the help of EDA(Exploratory Data Analysis) and ALS (Alternative Least Squares) which optimizes a users recommendations taking into considerations an account`s view history and uses matrix optimization to give the best possible recommendations.