Crypto-Currency-Predictor
This machine-learning algorithm takes in data from the last 60 days and tries to predict tomorrow's price of any crypto you ask it.
Synapse Machine Learning SynapseML (previously MMLSpark) is an open source library to simplify the creation of scalable machine learning pipelines. Sy
SKlearn_to_MLFLow In this Repo a simple Sklearn Model will be trained and pushed to MLFlow Install This Repo is based on poetry python3 -m venv .venv
SageMaker Python SDK SageMaker Python SDK is an open source library for training and deploying machine learning models on Amazon SageMaker. With the S
Combines MLflow with a database (PostgreSQL) and a reverse proxy (NGINX) into a multi-container Docker application (with docker-compose).
pytools is an open source library containing general machine learning and visualisation utilities for reuse, including: Basic tools for API developmen
The collaboration platform for Machine Learning MLReef is an open source ML-Ops platform that helps you collaborate, reproduce and share your Machine
Decision_Tree_Regression I implemented the decision tree regression algorithm on Python. Unlike regular linear regression, this algorithm is used when
Predico Disease Prediction system based on symptoms provided by patient- using Python-Django & Machine Learning
PySpark-Bank-Churn Surname: corresponds to the record (row) number and has no effect on the output. CreditScore: contains random values and has no eff
Common machine learning models' hyperparameter tuning This repo is for a collection of hyper-parameter tuning for "common" machine learning models, in
timemachines Autonomous, univariate, k-step ahead time-series forecasting functions assigned Elo ratings You can: Use some of the functionality of a s
A Microsoft Azure Web App project named Covid 19 Predictor using Machine learning Model (Random Forest Classifier Model ) that helps the user to identify whether someone is showing positive Covid sym
This project has Classification and Clustering done Via kNN and K-Means respectfully. It later tests its efficiency via F1/accuracy/recall/precision for kNN and Davies-Bouldin Index for Clustering. T
I have collected data about a set of patients, all of whom suffered from the same illness. During their course of treatment, each patient responded to one of 5 medications, Drug A, Drug B, Drug c, Dr
Auto-ML tool specialized in detecting of outliers Description This tool will allows you, with a Dash visualization, to compare 10 models of machine le
To-Be is a machine learning challenge on CodaLab Platform about Mortality Prediction. The challenge aims to adress the problems of medical imbalanced data classification.
Apple-voice-recognition Machine Learning How does Siri work? Siri is based on large-scale Machine Learning systems that employ many aspects of data sc
Polyglot Machine Learning example for scraping similar news articles In this example, we will see how we can work with Machine Learning applications w
Interactive Parallel Computing with IPython ipyparallel is the new home of IPython.parallel. ipyparallel is a Python package and collection of CLI scr
Model Serving Made Easy BentoML is a flexible, high-performance framework for serving, managing, and deploying machine learning models. Supports multi