June 28, 2021 Machine Learning

Objective of the repository is to learn and build machine learning models using Pytorch

30 Days Of Machine Learning Using Pytorch Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch List of Algorithms Covered 📌 Day 1 – Linear Regression 📌 Day 2 – Logistic Regression 📌 Day 3 – Decision Tree 📌 Day 4 – KMeans Clustering 📌 Day 5 – Naive Bayes 📌 Day 6 – K Nearest Neighbour (KNN) 📌 Day 7 – Support Vector Machine 📌 Day 8 – Tf-Idf Model 📌 […]

June 28, 2021 Visualization

Creating publication-quality figures with Matplotlib

matplotlib_for_papers Handout for the tutorial “Creating publication-quality figures with matplotlib” This repository contains the handout (and the source of the handout) for the tutorial “Creating publication-quality with Python and Matplotlib”, given at the Alife 2014 conference. Contributions are welcomed: feel free to clone and send pull requests. Examples of figures: Reference Tonelli, Paul, and Jean-Baptiste Mouret. “On the relationships between generative encodings, regularity, and learning abilities when evolving plastic artificial neural networks.” PloS one 8.11 (2013): e79138. Reference Clune*, Jeff, […]

June 28, 2021 Python

Reverse Python Lists: Beyond .reverse() and reversed()

Sometimes you need to process Python lists starting from the last element down to the first—in other words, in reverse order. In general, there are two main challenges related to working with lists in reverse: To meet the first challenge, you can use either .reverse() or a loop that swaps items by index. For the second, you can use reversed() or a slicing operation. In the next sections, you’ll learn about different ways to accomplish both in your code. Reversing […]

June 28, 2021 Advanced, NLP, Text

Part 18: Step by Step Guide to Master NLP – Topic Modelling using LDA (Probabilistic Approach)

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 part of this series, we completed our discussion on pLSA, which is a probabilistic framework for Topic Modelling. But we have seen some of the limitations of pLSA, so to resolve those limitations LDA comes into the picture. So, In this article, we will discuss the probabilistic or Bayesian approach to […]

June 28, 2021 NLP, Terminology

Issue #136 – Neural Machine Translation without Embeddings

28 Jun21 Issue #136 – Neural Machine Translation without Embeddings Author: Dr. Jingyi Han, Machine Translation Scientist @ Language Weaver Introduction Nowadays, Byte Pair Encoding (BPE) has become one of the most commonly used tokenization strategies due to its universality and effectiveness in handling rare words. Although many previous works show that subword models with embedding layers in general achieve more stable and competitive results in neural machine translation (NMT), character-based (see issue #60) and Byte-based subword (see issue #64) […]

June 27, 2021 JupyterLab

109 Python Problems for CCPS 109

PythonProblems This repository contains the problem specifications, the automated tester and the necessary data files for the graded lab problems for the course CCPS 109 Computer Science I, as taught by Ilkka Kokkarinen for the Chang School of Continuing Education, Ryerson University, Toronto, Canada. Write all your functions one by one into the same file labs109.py so that the acceptance tester script tester109.py can find them. This tester will execute the automated acceptance tests precisely for the functions implemented in […]

June 27, 2021 Command-line Tools

Declarative CLIs with argparse and dataclasses

argparse_dataclass Declarative CLIs with argparse and dataclasses. Features Features marked with a ✓ are currently implemented; features marked with a ⊘ are not yet implemented. [✓] Positional arguments [✓] Boolean flags [✓] Integer, string, float, and other simple types as arguments [✓] Default values [✓] Arguments with a finite set of choices [⊘] Subcommands [⊘] Mutually exclusive groups Examples Using dataclass decorator >>> from argparse_dataclass import dataclass >>> @dataclass … class Options: … x: int = 42 … y: bool […]

June 27, 2021 Terminal

Proper project management with Taskwarrior in vim

Taskwiki Proper project management in vim. Standing on the shoulders of vimwiki and Taskwarrior Installation Make sure you satisfy the requirements Vim 7.4 or newer, with +python or +python3 (NeoVim is also supported) Vimwiki (the dev branch) git clone https://github.com/vimwiki/vimwiki ~/.vim/bundle/ –branch dev Taskwarrior (version 2.4.0 or newer), install either from sources or using your package manager sudo dnf install task tasklib (the develop branch), Python library for Taskwarrior. sudo pip3 install –upgrade -r requirements.txt For neovim users: Note that […]

June 27, 2021 PyPI

Python ctypes wrapper around SDL2

PySDL2 PySDL2 is a pure Python wrapper around the SDL2, SDL2_mixer, SDL2_image, SDL2_ttf, and SDL2_gfx libraries. Instead of relying on C code, it uses the built-in ctypes module to interface with SDL2, and provides simple Python classes and wrappers for common SDL2 functionality. Installation PySDL2 is easy to install and integrate within your own projects. To install or update to the latest version, simply run one of the following commands in a terminal: # Install latest stable version from PyPI […]

June 27, 2021 Password

Create a password trought the command line with python

password_generator Password Generator allow you to create a password trough your terminal. Install Requirement pip install requirements.txt make sure to be in the parent folder and to have a virtual envrionment Usage Use without interactive command line interface python app/password_generator.py [password lenght] #if you are in the parent folder python password_generator.py [password lenght] #if you are in the app folder passowrd_generator.py [password lenght] #if you are in the app folder Use with interactive command line interface python app/password_generator.py #if you […]

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