There are 1 repository under mashine-learning topic.
The repository provides links to collections of influential and interesting research papers from top AI conferences, with open-source code to promote reproducibility and provide detailed implementation insights beyond the scope of the article. Stay up to date with the latest advances in AI research!
Course included such topics, as Data Preprocessing, Exploratory Data Analysis (EDA), Statistical Data Analysis (SDA), Data Collection and Storage (PostgreSQL), Business Analytics, Making Business Decisions Based on Data (Hypotheses testing), How to Tell a Story Using Data (Presentation and Data Visualization - Maplotlib, Seaborn, Plotly), Automation (Dash, Tableau), Forecasts and Predictions, 2 Integrated projects.
Moscow hackathon 2022. Task: development of a service for calculating the price of real estate. Result: 2nd place
Developing ML model predicting bank' customer inclination to open a deposit
Amazing Object Tracking
Some interesting topics in image processing
Данный проект направлен на демонстрацию навыков работы с GitHub и IDE
Performance Predictions of Spark Jobs with Machine Learning Tasks Using Various Artificial Intelligence Models
Band Gap Prediction for low-dimensional antimony(III) and bismuth(III) halides with 1D-anions.
Telegram-бот, который помогает администратору салона взаимодействовать с клиентами
A Text Generation AI made with Tensorflow
corenlp basic example
Config files for my GitHub profile.
This is my internship project as a MACHINE LEARNING Intern at Bharat intern company Task-1 Iris Flowers Classification
Predicted mental health and discovered its association with population density, income, water, and land features using machine learning models.
Kohanen SOM using ANN to identify clustering of amplitude roughness parameters
IA Python Project
Using SparkSQL, determined key metrics about home sales data. Then, I used Spark to create temporary views, partition the data, cache and uncache a temporary table, and verify that the table has been uncached.
I used lending data to create machine learning models that classify the risk level of given loans. Specifically, I compared the performance of the Logistic Regression model and the Random Forest Classifier.
This repo was made to work on the creation of my master thesis
A Machine-Learning Model to Predict the Patient diagnosis based on the given features from a dataset.
ML modeling for house price prediction in Belarus