Deep Learning, NLP, NMT, AI, ML
PwdGen PwdGen is a Python Tkinter tool for generating secure 16 digit passwords. Installation Simply install requirements pip install -r requirements.txt Usage python main.py After that generate your password and copy it to your clipboard. Screenshots GitHub https://github.com/zJairO/PwdGen
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EntropyHub Information and uncertainty can be regarded as two sides of the same coin: the more uncertainty there is, the more information we gain by removing that uncertainty. In the context of information and probability theory, Entropy quantifies that uncertainty. The concept of entropy has its origins in classical physics under the second law of thermodynamics, a law considered to underpin our fundamental understanding of time in physics. Attempting to analyse the analog world around us requires that we measure […]
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Option Valuation with Python An option valuation webapp in Python. Models Installation Clone this repository : git clone https://github.com/romaincaraes/option-valuation-python cd option-valuation-python You may want to use a virtual environment to keep a clean Python installation : python3 -m venv venv/ source venv/bin/activate Install the required dependencies : pip3 install -r requirements.txt Usage To use the Option Valuation web app, run the option.py script in option-valuation/ folder : cd option-valuation streamlit run option.py A new tab should open in your browser […]
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sports_maps A lib version of the sports master planning code. Aimed a producing sport overviews for certain cities. Demoes of reports for Sedan and the Kremlin Bicetre. Repository Ownership Practice: Sport Sector: Asset management Original Author(s): Luc Jonveaux Contact Details for Current Repository Owner(s): [email protected] Data Running the Code Relatively straightforward import gpdSport data = gpdSport.dataSets() DATA = data.CreateDF(“data/) data.CreateVille(8409); #produces the an analysis for SEDAN fig = data.CreateMap(ZOOM=12) # creates a map, with a basemap zoom at 12 data.createReport(); […]
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HTTPie HTTPie (pronounced aitch-tee-tee-pie) is a command-line HTTP client. Its goal is to make CLI interaction with web services as human-friendly as possible. HTTPie is designed for testing, debugging, and generally interacting with APIs & HTTP servers. The http & https commands allow for creating and sending arbitrary HTTP requests. They use simple and natural syntax and provide formatted and colorized output. GitHub https://github.com/httpie/httpie
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PoseCamera PoseCamera is python based SDK for multi human pose estimation through RGB webcam. Install install posecamera package through pip pip install posecamera If you are having issues with the installation on Windows OS then check this page Usage See Google colab notebook https://colab.research.google.com/drive/18uoYeKmliOFV8dTdOrXocClCA7nTwRcX?usp=sharing draw pose keypoints on image import posecamera import cv2 det = posecamera.pose_tracker.PoseTracker() image = cv2.imread(“example.jpg”) pose = det(image) for name, (y, x, score) in pose.keypoints.items(): cv2.circle(image, (int(x), int(y)), 4, (255, 0, 0), -1) cv2.imshow(“PoseCamera”, image) cv2.waitKey(0) […]
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bibliothecula document organizer with tags and full-text-search, in a simple and clean sqlite3 schema. bibliothēcula f (genitive bibliothēculae); first declension (Late Latin) small library small collection of books document database with tags and full-text-search, in a simple and clean sqlite3 schema Organise documents with tags and other metadata with the option of storing multiple files per document. See the database schema and the documentation. Uses Organise journal articles for bibliographies Organise e-books Store plain text notes with automatic full-text search […]
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3D Multi-Object Tracker This project is developed for tracking multiple objects in 3D scene. The visualization code is from here. Features Fast: currently, the codes can achieve 700 FPS using only CPU (not include detection and data op), can perform tracking on all kitti val sequence in several seconds. Support both online and global implementation. The overall framework of design is shown below: Kitti Results Results on the Kitti tracking val seq [1,6,8,10,12,13,14,15,16,18,19] using second-iou and point-rcnn detections. We followed […]
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ElegantRL ElegantRL is featured with lightweight, efficient and stable, for researchers and practitioners. Lightweight: The core codes <1,000 lines (check elegantrl/tutorial), using PyTorch (train), OpenAI Gym (env), NumPy, Matplotlib (plot). Efficient: performance is comparable with Ray RLlib. Stable: as stable as Stable Baseline 3. Currently, model-free deep reinforcement learning (DRL) algorithms: DDPG, TD3, SAC, A2C, PPO, PPO(GAE) for continuous actions DQN, DoubleDQN, D3QN for discrete actions For DRL algorithms, please check out the educational webpage OpenAI Spinning Up. File Structure […]
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Machine Learning for Beginners – A Curriculum 🌍 Travel around the world as we explore Machine Learning by means of world cultures 🌍 Azure Cloud Advocates at Microsoft are pleased to offer a 12-week, 24-lesson curriculum all about Machine Learning. In this curriculum, you will learn about what is sometimes called classic machine learning, using primarily Scikit-learn as a library and avoiding deep learning, which is covered in our forthcoming ‘AI for Beginners’ curriculum. Pair these lessons with our forthcoming […]
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