Deep Learning, NLP, NMT, AI, ML
domonic domonic is a library to generate HTML with python 3. There’s an evolving DOM API and some other cool features. Can be used as a fast prototyping tool. Contains several evolving packages: (but by no means are any of them complete) • html : Generate html with python 3 😎 • dom : DOM API in python 3 😲 • javascript : js API in python 3 😳 • terminal : call terminal commands with python3 😱 (see at […]
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Random database/dataframe generator Often, beginners in SQL or data science struggle with the matter of easy access to a large sample database file (.DB or .sqlite) for practicing SQL commands. Would it not be great to have a simple tool or library to generate a large database with multiple tables, filled with data of one’s own choice? After all, databases break every now and then and it is safest to practice with a randomly generated one 🙂 While it is […]
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MoniGoMani MoniGoMani aims to be more than just a conventional strategy, it’s a framework to “easily” find a profitable strategy configuration in any market! Without the need to do any programming. However, you will need to know some Technical Analysis and be able to pull your own conclusions from your test-results, this is not just an easy copy/paste. MGM (MoniGoMani) derives itself from other strategies by its use of something I called “weighted signals”. Each signal has its own weight […]
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pybullet-planning (previously ss-pybullet) A repository of PyBullet utility functions for robotic motion planning, manipulation planning, and task and motion planning (TAMP). This repository was originally developed for the PDDLStream (previously named STRIPStream) approach to TAMP. With the help of Yijiang Huang, a stable and documented fork of pybullet-planning named pybullet_planning is available through PyPI. However, new features will continue to be introduced first through pybullet-planning. Installation Install for macOS or Linux using: pybullet-planning is intended to have ongoing support for […]
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10 Jun21 Issue #134 – A Targeted Attack on Black-Box Neural MT in Robustness, The Neural MT Weekly Author: Dr. Karin Sim, Machine Translation Scientist @ Iconic Introduction Last week we looked at how neural machine translation (NMT) systems are naturally susceptible to gender bias. In today’s blog post we look at the vulnerability of an NMT system to targeted attacks, which could result in unsolicited or harmful translations. Specifically we report on work by Xu et al., 2021, which […]
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Inferoxy Inferoxy is a service for quick deploying and using dockerized Computer Vision models. It’s a core of EORA’s Computer Vision platform Vision Hub that runs on top of AWS EKS. Why use it? You should use it if: You want to simplify deploying Computer Vision models with an appropriate Data Science stack to production:all you need to do is to build a Docker imagewith your model including any pre- and post-processing steps and push it into an accessible registry […]
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train-CLIP A PyTorch Lightning solution to training CLIP from scratch. Usage 🚂 This training setup is easily usable right outside the box! Simply provide a training directory or your own dataset and we’ve got the rest covered. To train a model just specify a name from the paper name and tell us your training folder and batch size. All possible models can be seen in the yaml files in models/config python train.py –model_name RN50 –folder data_dir –batchsize 512 Training with […]
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Delta Sharing Delta Sharing is an open protocol for secure real-time exchange of large datasets, which enables organizations to share data in real time regardless of which computing platforms they use. It is a simple REST protocol that securely shares access to part of a cloud dataset and leverages modern cloud storage systems, such as S3, ADLS, or GCS, to reliably transfer data. With Delta Sharing, a user accessing shared data can directly connect to it through pandas, Tableau, Apache […]
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New to Streaming Scraper An in-progress web scraping project built with Python, R, and SQL. A web scraping project that retrieves TV and movie data from two sources, then transforms and stores data in a MySQL database. Data are retrieved from two different data sources: What’s on Netflix (WON) and Rotten Tomatoes (RT). RT data are cleaned and transformed with Python, while WON data are cleaned and transformed with R. All data are piped into a MySQL database, then retrieved […]
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Eight Puzzle CLI 8-piece command-line puzzle game developed for the Artificial Intelligence discipline. Written in python, this project aims to apply the studied concepts and implement a simple intelligent agent that can solve the game. Project execution Dependencies Execution Automatic agents Two automatic agents are implemented that use two “brute force” search algorithms: Breadth-first Search Algorithm – BFS Width search, graph/tree search algorithm where the exploration of all neighboring vertices is prioritized before traversing to the next depth, until a […]
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