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intro-to-computer-vision-with-python-opencv

An Introduction to Computer Vision using OpenCV with Python Bindings

introduction-to-linear-programming

Introduction to Linear Programming with Python

jupyter

Jupyter metapackage for installation, docs and chat

jupyter-notebooks

labelimg

:metal: LabelImg is a graphical image annotation tool and label object bounding boxes in images

labelme

Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).

libsvm

lingvo

Lingvo

livy

Livy is an open source REST interface for interacting with Apache Spark from anywhere

lpinpython

Linear Programming in Python (Using PuLP)

ludwig

Ludwig is a toolbox built on top of TensorFlow that allows to train and test deep learning models without the need to write code.

machine-learning-systems-design

A booklet on machine learning systems design with exercises

machine-learning-systems-design-1

机器学习系统设计案例与测试 Machine Learning Systems Design Cases & Tests

machine_learning_system_design

Links to company blog posts

make-sense

Free to use online tool for labelling photos. https://makesense.ai

market_analysis-predicting_customer_churn

marketbasketanalysis

metashape-scripts

Python scripts for Metashape (former PhotoScan)

ml-system-design-pattern

System design patterns for machine learning

mlops-template

mlops template

modeling_nyc_taxis_tip_trends

models

Models and examples built with TensorFlow

mysql_to_pandas

mysqltopandas

Connecting MySQL to Pandas

nbbrowserpdf

LaTeX-free PDF generation from Jupyter Notebooks

nbconvert-reportlab

nnlib

Matlab implentations of Neural Network and Learning Modules (MLP Network, RBF Network and SVM cross validation)

object-detection

Introduction The project presents an efficient method for object detection and demonstrates its use for real-time vision on-board vehicles. The work is closely based on Paul Viola’s face detection method [1], except that the system here was trained to detect objects related to traffic in order to assist the auto pilot on smart vehicles. The idea was adapted from D M Gavrila’s paper [2] REAL-TIME OBJECT DETECTION FOR "SMART" VEHICLES. Objective The target is to create Haar feature-based cascade classifiers by training the system with an appropriate amount of traffic related information in order to detect vehicles, pedestrians and traffic signs in real-time. Thus, this system in addition to driving assistance/collision avoidance, could further find its application in tracking and recognition.

object-recognition-sift-surf

object_detection_demo_live

This is the code for the "How to do Object Detection with OpenCV" live session by Siraj Raval on Youtube