Topic: applied-machine-learning Goto Github
Some thing interesting about applied-machine-learning
Some thing interesting about applied-machine-learning
applied-machine-learning,Work has been done on COVID-19 Bangladesh situation .Where Data Analysis, Data Visualization, Supervised Learning and Unsupervised Learning are used.
applied-machine-learning,Machine Learning and Deep Learning in Bioinformatics - Master's thesis repository
applied-machine-learning,This project contains the code to perform a task of Particle identification (PID) in Astrophysics, comparing Deep Learning and Classical Machine Learning approaches. Data are provided by Agile team (http://agile.rm.iasf.cnr.it/) and the goal of the analysis is to provide a Statistical model which is able to distinguish gamma-ray photon for background particles.
applied-machine-learning,Curated list of technical blogs on machine learning · AI/ML/DL/CV/NLP/MLOps
applied-machine-learning,Python3 implementation of gender detection from speech using GMM.
applied-machine-learning,📚「@MaiweiAI」Studying papers in the fields of computer vision, NLP, and machine learning algorithms every week.
Home Page: https://maiweiai.github.io
applied-machine-learning,📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
applied-machine-learning,Python solutions to solve practical business problems.
applied-machine-learning,Summer is the best season in the real estate market and housing prices vary based on a number of features. Data from 2 such Summers is taken about the Kings County Housing Prices. Two Jupyter Notebooks depicting the various Regression models is used to depict how the number of bedrooms, waterfront location, total area in square feet, etc. affect the housing prices. Machine Learning with Python is used throughout the course of the project. Jupyter Notebooks give complete detail of implementation.
applied-machine-learning,This repository contains course files and assignments of Coursera.
applied-machine-learning,Courses I have completed in Coursera
applied-machine-learning,This repo has all the files that I used during the studies of ML and DS
applied-machine-learning,[2021 Summer Research in Applied Machine Learning] Built two desktop apps using PyQt5 to perform pixel-classification with k-means clustering to explore the chemical composition of objects scanned with high-resolution x-rays.
applied-machine-learning,Mask R-CNN Model to detect the area of damage on a car. The rationale for such a model is that it can be used by insurance companies for faster processing of claims if users can upload pics and they can assess damage from them. This model can also be used by lenders if they are underwriting a car loan especially for a used car.
applied-machine-learning,Automated the process of training time-series data with multiple Machine Learning and Stats Models to output the most accurate forecast result
applied-machine-learning,Implementation of various of algorithms such as EM for Topic Modeling, High Dim. Classification, PCA, etc. described in "Applied Machine Learning" by David Forsyth
applied-machine-learning,A curated list of resources to deep dive into the intersection of applied machine learning and threat detection.
applied-machine-learning,A collection of awesome software, learning tutorials, theoretical resources, books and videos, best practices in applied cryptography.
applied-machine-learning,📚 Curated collection of blogs and papers on how different companies are using machine learning in production for better customer support.
applied-machine-learning,📚 Curated list of machine learning engineering blogs.
applied-machine-learning,The goal of this project is to analyze the dynamics of small fishing vessel fleets and provide information to help policy-makers design legislation to prevent Illegal, Unreported, and Unregulated (IUU) fishing.
applied-machine-learning,Conducted data analysis using statistical tools and complex visualizations; trained logistic regression, k-nn, kernelized svm, and random forest models; performed hyperparameter tuning and error analysis. Tech: Python (Seaborn, Matplotlib, Pandas, Scikit-Learn)
applied-machine-learning,This repository contains my well documented solutions to Applied Machine Learning with Python course on coursera by University of Michigan
applied-machine-learning,Some of my work as an undergraduate Informatics student (2017-2021)
Home Page: https://themelinakz.github.io/UniWork/
applied-machine-learning,This Repo contains - Starter files, Coursework, Programming Assignments for the course --> Applied Machine Learning in Python, University of Michigan [COURSERA]
applied-machine-learning,Unity's Privacy-Preserving Novel Human Body Model Trained Solely on Synthetic Data and Corresponding Dense Anthropometric Measurements
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
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Bring data to life with SVG, Canvas and HTML. 📊📈🎉
Some thing interesting about web. New door for the world.
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Some thing interesting about visualization, use data art
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We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
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Data-Driven Documents codes.
China tencent open source team.