Deep Learning workshop including image classification, face recognition, Object detection, language modelling, image captioning and neural machine translation.

snrazavi Last update: Dec 20, 2023

Deep Learning in Python (PyTorch)

HamYad Research Lab., University of Tabriz (2018)
Course website
YouTube videos (in Persian)
All the implementations are based on PyTorch. To install PyTorch, please see here.

Updated (09/09/2021)

Week 01, week 02, week 03 updated to work with recent versions of PyTorch.

Week 0: Introduction

Part 1: Machine Vision

Week 1: Image Classification

Week 2: Face Recognition

Week 3: Object Localization and Classification

Week 4: Object Detection (Yolo2)

Part 2: Natural Language Processing

Week 5: Text Classification (Sentiment Analysis)

Week 6: Language Modelling

Week 7: Image Captioning

Week 8: Machine Translation (En to Per)

Assignments:

Tags:

Owner

snrazavi

GitHub Repository https://github.com/snrazavi

Programmed the SDN controller to monitor the traffic, predict the traffic behaviour and detect DDOS traffic in the cloud network and mitigate it. Machine learning SVM algorithm was used to predict the malicious traffic in the network, achieved an accuracy of 98% and detection rate of 100%. Technologies Used are, SDN, ML SVM, Openflow, Ryu controller, Python, Mininet, iperf, hping3, linux commands.

Stress classifier with AutoML

This repository presents an automated machine learning approach in Python to create a stress monitoring system with data from devices such as fitness trackers. With the rising popularity of trackers …

Solutions to the 'Applied Machine Learning In Python' Coursera course exercises

PyDeep is a machine learning / deep learning library with focus on unsupervised learning. The library has a modular design, is well documented and purely written in Python/Numpy. This allows you to understand, use, modify, and debug the code easily. Furthermore, its extensive use of unittests assures a high level of reliability and correctness.

Welcome ################################## PyDeep is a machine learning / deep learning library with focus on unsupervised learning. The library has a modular design, is well documented and purely wr…

A 50-Day Guide to Becoming a Data Scientist with Python, SQL, and Machine Learning

Welcome to the Data Science course! Over the next 50 days, you will learn a wide range of topics related to Python programming, data science, and machine learning. These topics will be covered in a v…

splearn: package for signal processing and machine learning with Python. Contains tutorials on understanding and applying signal processing.

This repository contains tutorials on understanding and applying signal processing using NumPy and PyTorch. In order to begin the signal processing adventure, we need to understand what we are dealin…

{Python}: Detect and extract the license plate of vehicles using Machine Learning and Image Processing Techniques

This project aims to utilize Machine Learning and Image Processing techniques to detect/extract license plates of vehicle given an image. This module is aimed to extract features from a license plate…

Python script to generate fake datasets optimized for testing machine learning/deep learning workflows

These datasets also work well when testing against AutoML approaches, as it has several traps just for that use case. The generated datasets have the following properties which test the limits of ML/…

Repo where I recreate some popular machine learning models from scratch in Python

This repository is for educational purposes. While the efficiency of the code or completeness is not as good as the one you could find in a library like sklearn, the simplification of the algorithm a…

Machine learning in Python for stock market and forex market predictions (fully functional)

OPEN-SOURCE PROJECT | Machine learning in Python and MQL4 for stock market and forex market predictions and fully automated trading.