394 Open source projects that are alternatives of or similar to pedestrian-detection

Source code of the model used in Tensorflow Speech Recognition Challenge (https://www.kaggle.com/c/tensorflow-speech-recognition-challenge). The solution ranked in top 5% in private leaderboard.

All the slides, accompanying code and exercises all stored in this repo. 🎈

Intel(R) Extension for Scikit-learn is a seamless way to speed up your Scikit-learn application

Class-imbalanced / Long-tailed ensemble learning in Python. Modular, flexible, and extensible. | 模块化、灵活、易扩展的类别不平衡/长尾机器学习库

Kaggle Struggle

Face/Beauty Rating with both the traditional ML approaches and Convolutional Neural Network Approach

Applying machine learning to predict loan charge-offs on LendingClub.com

Explore machine learning models. Leveraging scikit-learn's models and exposing their behaviour through API

a delightful machine learning tool that allows you to train, test, and use models without writing code

Formed trajectories of sets of points.Experimented on finding similarities between trajectories based on DTW (Dynamic Time Warping) and LCSS (Longest Common SubSequence) algorithms.Modeled trajectories as strings based on a Grid representation.Benchmarked KNN, Random Forest, Logistic Regression classification algorithms to classify efficiently t…

I am taking up the #100DaysOfMLCode Challenge 😎

Clustering routines for the unit sphere

No description or website provided.

A basic introduction to machine learning (one day training).

Content Based Music Recommendation Service

A docker-based starter kit for machine learning via jupyter notebooks. Designed for those who just want a runtime environment and get on with machine learning. Docker tags:

利用Logistic回归实现信用卡欺诈检测

A scikit-learn compatible library for anomaly detection

"20 newsgroups" dataset - Text Classification using Multinomial Naive Bayes in Python.

Porn images detector with python, tensorflow, scikit-learn and opencv.

Tutorial on deploying machine learning models to production

Python Client and Toolkit for DataFrames, Big Data, Machine Learning and ETL in Elasticsearch

This project has 3 goals: To find out the best machine learning pipeline for predicting ASD cases using genetic algorithms, via the TPOT library. (Classification Problem) Compare the accuracy of the accuracy of the determined pipeline, with a standard Naive-Bayes classifier. Saving the classifier as an external file, and use this file in a Flask…

📓 deepleaning and cv notes.

C++ Implementation of Image Super-Resolution using Convolutional Neural Network

This is a repository for the tutorial materials in machine learning (COMP4211) in HKUST.

Automatically Build Multiple ML Models with a Single Line of Code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.

No description or website provided.

Keras implementation of CNN, DeepConvLSTM, and SDAE and LightGBM for sensor-based Human Activity Recognition (HAR).

skrobot is a Python module for designing, running and tracking Machine Learning experiments / tasks. It is built on top of scikit-learn framework.

DeepCrack: Learning Hierarchical Convolutional Features for Crack Detection

[ECCV 2020] Codes and MultiviewX dataset for "Multiview Detection with Feature Perspective Transformation".

⏱ Benchmarks of machine learning inference for Go

Extensive tutorials for the Advanced NLP Workshop in Open Data Science Conference Europe 2020. We will leverage machine learning, deep learning and deep transfer learning to learn and solve popular tasks using NLP including NER, Classification, Recommendation \ Information Retrieval, Summarization, Classification, Language Translation, Q&A and T…

PipelineAI Kubeflow Distribution

Training time estimation for scikit-learn algorithms

Traffic Sign Recognition by Convolutional Neural Network (TensorFlow)

Deanonymizing Tor or VPN users with website fingerprinting and machine learning.

Implementation of cartoon GAN [Chen et al., CVPR18] with pytorch

Machine learning in Matlab using scikit-learn syntax

A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Climate / Energy, Automotives, Retail, Pharma, Medicine, Healthcare, Policy, Ethics and more.

A complete one stop solution for all the problems of Rural area people. 👩🏻‍🌾

🍊 📊 💡 Orange: Interactive data analysis

A scikit-learn compatible implementation of hyperband

A drop-in replacement for Scikit-Learn’s GridSearchCV / RandomizedSearchCV -- but with cutting edge hyperparameter tuning techniques.

基于scikit-learn实现对新浪新闻的文本分类，数据集为100w篇文档，总计10类，测试集与训练集1:1划分。分类算法采用SVM和Bayes，其中Bayes作为baseline。

Machine Learning and NLP: Text Classification using python, scikit-learn and NLTK

Introduction to Machine Learning with Time Series at PyData Festival Amsterdam 2020

Machine Learning Containers for NVIDIA Jetson and JetPack-L4T

python library implementing ensemble methods for regression, classification and visualisation tools including Voronoi tesselations.

MNIST digit classification with scikit-learn and Support Vector Machine (SVM) algorithm.

Public reusable components for Polyaxon

Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.

🤓🔮🔬 Emoji prediction from a text using machine learning

Movie Recommendation Chatbot provides information about a movie like plot, genre, revenue, budget, imdb rating, imdb links, etc. The model was trained with Kaggle’s movies metadata dataset. To give a recommendation of similar movies, Cosine Similarity and TFID vectorizer were used. Slack API was used to provide a Front End for the chatbot. IBM W…

This repository is a recommended track, designed to get started with Machine Learning.

https://dodiku.github.io/audio_noise_clustering/results/ ==> An experiment with a variety of clustering (and clustering-like) techniques to reduce noise on an audio speech recording.

REST API (and possible UI) for Machine Learning workflows

Bay Area WiMLDS scikit-learn open source sprint (Nov 2, 2019)

Extracts key terminology (n-grams) from any large collection of documents (>1000) and forecasts emergence