Transformer

Unofficial TensorFlow implementation of the Keyword Spotting Transformer model

Keyword Spotting Transformer This is the unofficial TensorFlow implementation of the Keyword Spotting Transformer model. This model is used to train on the 35 words speech command dataset Paper : Keyword Transformer: A Self-Attention Model for Keyword Spotting Model architecture Download the dataset To download the dataset use the following command wget https://storage.googleapis.com/download.tensorflow.org/data/speech_commands_v0.02.tar.gz mkdir data mv ./speech_commands_v0.02.tar.gz ./data cd ./data tar -xf ./speech_commands_v0.02.tar.gz cd ../ Setup virtual environment virtualenv -p python3 venv source ./venv/bin/activate Install dependencies pip install -r requirements.txt […]

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Workflow

AI and Machine Learning workflows on Anthos Bare Metal

AI and Machine Learning workflows using TensorFlow on Anthos Bare Metal. TensorFlow is one of the most popular ML frameworks (10M+ downloads per month) in use today, but at the same time presents a lot of challenges when it comes to setup (GPUs, CUDA Drivers, TF Serving etc), performance tuning, cluster provisioning, maintenance, and model serving. This work will showcase the easy to use guides for ML model serving, training, infrastructure, ML Notebooks, and more on Anthos Bare Metal. Terraform […]

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Wrapper

A simple request wrapper for the Pancake-Swap API

Python Pancakes A simple request wrapper for the Pancake-Swap API. Installation Install package # Using pip $ pip install pythonpancakes # Or from source $ git clone https://github.com/scottburlovich/pythonpancakes.git pythonpancakes $ cd pythonpancakes $ python3 setup.py install Import module into your project and initialize API class from pythonpancakes import PancakeSwapAPI ps = PancakeSwapAPI() Usage Please note, the API functionality currently exposed by PancakeSwap is quite basic. This package will be updated as they add new functionality. summary() Returns a dictionary containing […]

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Speech To Text

Chimera: Learning Shared Semantic Space for Speech-to-Text Translation

This is a Pytorch implementation for the “Chimera” paper Learning Shared Semantic Space for Speech-to-Text Translation https://arxiv.org/abs/2105.03095 (accepted by ACL Findings 2021), which aims to bridge the modality gap by unifying the task of MT (textual Machine Translation) and ST (Speech-to-Text Translation). It has achieved new SOTA performance on all 8 language pairs in MuST-C benchmark, by utilizing an external MT corpus. ![](https://github.com/Glaciohound/Chimera-ST/raw/main/chimera/resources/figs/method.png =100%x) This repository is up to now a nightly version, and is bug-prone because of code refactoring. […]

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Visualization

Propuestas electorales de los candidatos a constituyentes, Chile 2021

textos-constituyentes propuestas electorales de los candidatos a constituyentes, Chile 2021 Programas descargados desde https://elecciones2021.servel.cl/informacion-general/ Metodología/Programación Inicialmente, bastaba con utilizar beautifulsoup + fitz en Python para descargar los archivos en formato PDF y extraer sus textos. Luego notamos que venían muchos vacíos, por corresponder a PDF escaneados (como el notable caso de una candidata del distrito 15 que subió su diploma). Para resolver este problema, recurrimos al servicio Transcribe de Amazon Cloud (con la librería boto3). GitHub https://github.com/sergiolucero/textos-constituyentes    

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Deep Learning

Guide & Examples to create deep learning gstreamer plugins and use them in your pipeline

Guide & Examples to create deeplearning gstreamer plugins and use them in your pipeline Thanks to the work done by @jackersson. In this repository we have taken inspirations from: gstreamer-python gst-plugins-tf We have currently tested our code on Ubuntu 18.04. You can also refer to the official installation document for your linux flavor. Packages Required sudo apt install cmake m4 git build-essential sudo apt install libssl-dev libcurl4-openssl-dev liblog4cplus-dev Gstreamer Installation sudo apt-get install libgstreamer1.0-0 gstreamer1.0-plugins-base gstreamer1.0-plugins-good gstreamer1.0-plugins-bad gstreamer1.0-plugins-ugly gstreamer1.0-libav gstreamer1.0-doc […]

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Matplotlib

A Python library for plotting hockey rinks with Matplotlib

Hockey Rink A Python library for plotting hockey rinks with Matplotlib. Installation pip install hockey_rink Current Rinks The following shows the custom rinks currently available for plotting. from hockey_rink import NHLRink, IIHFRink, NWHLRink import matplotlib.pyplot as plt fig, axs = plt.subplots(1, 3, sharey=True, figsize=(12, 6), gridspec_kw={“width_ratios”: [1, 98.4/85, 1]}) nhl_rink = NHLRink(rotation=90) iihf_rink = IIHFRink(rotation=90) nwhl_rink = NWHLRink(rotation=90) axs[0] = nhl_rink.draw(ax=axs[0]) axs[1] = iihf_rink.draw(ax=axs[1]) axs[2] = nwhl_rink.draw(ax=axs[2]) The NWHL logo comes from the NWHL site. Customization There is also room […]

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Machine Learning

A New, Interactive Approach to Learning Python

The Python Workshop This is the repository for The Python Workshop, published by Packt. It contains all the supporting project files necessary to work through the course from start to finish. Requirements and Setup To get started with the project files, you’ll need to: Install Jupyter on Windows, Mac, Linux Install Anaconda on Windows, Mac, Linux Install Docker About The Python Workshop More than just a Python guide for beginners, The Python Workshop takes you through the full spectrum of […]

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Advanced, NLP, Text

Part 16 : Step by Step Guide to Master NLP – Topic Modelling using LSA

This article was published as a part of the Data Science Blogathon Introduction This article is part of an ongoing blog series on Natural Language Processing (NLP). In the previous article, we completed a basic technique of Topic Modeling named Non-Negative Matrix Factorization. So, In continuation of that part now we will start our discussion on another Topic modeling technique named Latent Semantic Analysis. So, In this article, we will deep dive into a Topic Modeling technique named Latent Semantic Analysis […]

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Advanced, NLP, Text

Part 20: Step by Step Guide to Master NLP – Information Retrieval

This article was published as a part of the Data Science Blogathon Introduction This article is part of an ongoing blog series on Natural Language Processing (NLP). In the previous article, we completed our discussion on Topic Modelling Techniques. Now, in this article, we will be discussing an important application of NLP in Information Retrieval. So, In this article, we will discuss the basic concepts of Information Retrieval along with some of the models that are used in Information Retrieval. NOTE: […]

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