June 8, 2021 Database

A Python DB API and SQLAlchemy dialect for querying non-SQL resources like APIs

shillelagh Shillelagh is a Python DB API and SQLAlchemy dialect for querying non-SQL resources like APIs and files. You can use it to write queries like this: INSERT INTO “csv:///path/to/file.csv” SELECT time, chance_of_rain FROM “https://api.weatherapi.com/v1/history.json?key=XXX&q=London” WHERE strftime(‘%Y-%m-%d’, time) IN ( SELECT day FROM “https://docs.google.com/spreadsheets/d/1_rN3lm0R_bU3NemO0s9pbFkY5LQPcuy1pscv8ZXPtg8/edit#gid=2064361835” ) The query above reads holidays from a Google Sheet, uses the days to get weather data from WeatherAPI, and writes the change of rain at each hour of the holidays into a (pre-existing) CSV file. […]

June 8, 2021 Data Analysis

A Python Framework for Modeling and Analysis of Signaling Systems

BioMASS Mathematical modeling is a powerful method for the analysis of complex biological systems. Although there are many researches devoted on producing models to describe dynamical cellular signaling systems, most of these models are limited and do not cover multiple pathways. Therefore, there is a challenge to combine these models to enable understanding at a larger scale. Nevertheless, larger network means that it gets more difficult to estimate parameters to reproduce dynamic experimental data needed for deeper understanding of a […]

June 8, 2021 Deep Learning

A Python library for secure and private Deep Learning

PySyft PySyft decouples private data from model training, using Federated Learning, Differential Privacy, and Encrypted Computation (like Multi-Party Computation (MPC) and Homomorphic Encryption (HE)) within the main Deep Learning frameworks like PyTorch and TensorFlow. Most software libraries let you compute over the information you own and see inside of machines you control. However, this means that you cannot compute on information without first obtaining (at least partial) ownership of that information. It also means that you cannot compute using machines […]

June 8, 2021 Python

Python Basics: Setting Up Python

Setting up Python is the first step to becoming a Python programmer. In this course, you’ll learn how to download and install Python for Windows, macOS, and Ubuntu Linux and how to open Python’s Integrated Development and Learning Environment, IDLE. There are many ways to install Python. You can download official Python distributions from Python.org, install from a package manager, and even install specialized distributions for scientific computing, Internet of Things, and embedded systems. This course focuses on official distributions, […]

June 8, 2021 Deep Learning, Intermediate, NLP, Unstructured Data

Generate Questions from Movies!

This article was published as a part of the Data Science Blogathon Have you ever thought of generating questions from the SRT files of Movies? I don’t know if we can use this but it is pretty exciting when I came to know as a beginner that we can do that. What is SRT? In simple terms, the subtitles you see in Amazon Prime, Netflix, Hotstar, HBO, etc are saved in a text file with (.srt) extension with timestamps. The timestamp […]

June 8, 2021 Beginner, Data Science, Machine Learning, NLP, Python, Text

Text Analytics of Resume Dataset with NLP!

This article was published as a part of the Data Science Blogathon Introduction We all have made our resumes at some point in time. In a resume, we try to include important facts about ourselves like our education, work experience, skills, etc. Let us work on a resume dataset today. The text we put in our resume speaks a lot about us. For example, our education, skills, work experience, and other random information about us are all present in a resume. […]

June 7, 2021 NLP

Deep Learning on Graphs for Natural Language Processing

June 6, 2021 By: Lingfei Wu, Yu Chen, Heng Ji, Yunyao Li Abstract This tutorial of Deep Learning on Graphs for Natural Language Processing (DLG4NLP) is timely for the computational linguistics community, and covers relevant and interesting topics, including automatic graph construction for NLP, graph representation learning for NLP, various advanced GNN based models (e.g., graph2seq, graph2tree, and graph2graph) for NLP, and the applications of GNNs in various NLP tasks (e.g., machine translation, natural language generation, information extraction and semantic […]

June 7, 2021 Data Visualization

Visualizing weather changes across the world using third party APIs and Python

Weather-Forecasting Python scripts were created to visualize the weather for over 500 cities across the world at varying distances from the equator. To understand weather patterns for forecasting, a series of scatter plots were created. The scatter plots depicted the relationship between Temperature versus Latitude, Humidity versus Latitude, Cloudiness versus Latitiude, and Wind Speed versus Latitude. One of the relationship is shown below: Linear regressions for each relationship were created separating them in Northern and Southern Hemispheres. More than 500 […]

June 7, 2021 Images

High-level API for attractive and descriptive image visualization in Python

seaborn-image Seaborn-image is a Python image visualization library based on matplotlib and provides a high-level API to draw attractive and informative images quickly and effectively. It is heavily inspired by seaborn, a high-level visualization library for drawing attractive statistical graphics in Python. Installation For latest release pip install seaborn-image For latest commit pip install git+https://github.com/SarthakJariwala/seaborn-image GitHub https://github.com/SarthakJariwala/seaborn-image

June 7, 2021 Tool

An all-purpose tool for working with code complexity metrics

Metrinome Metrinome is an all-purpose tool for working with code complexity metrics. It can be used as both a REPL and API, and includes: Converters to turn C++, Java, and Python code to Control Flow Graphs Metric calculators for NPath, Cyclomatic, and Path Complexity KLEE utilities to automatically analyze C++ code To get started, follow the guide in the wiki to pull the docker image and jump directly into the REPL. GitHub https://github.com/hmc-alpaqa/metrinome

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