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5 Popular Machine Learning algorithms
Machine Learning Source: Image by GDJ on Pixabay A machine learning algorithm is conceptually similar to any other algorithm in computer science. An ML algorithm is a data-driven process that is used to create a production-ready machine learning model. If you consider machine learning to be a train for accomplishing a job, then machine learning models are the engines that push the train. The (…)
18 Common Python Anti-Patterns I Wish I Had Known Before
You can learn as much from reading a bad code as you can from reading a good one Resources: https://docs.quantifiedcode.com/python-anti-patterns/index.html https://deepsource.io/blog/8-new-python-antipatterns/ https://github.com/quantifiedcode/python-anti-patterns https://docs.python-guide.org/writing/gotchas/#mutable-default-arguments (…)
Send HTTP Requests As Fast As Possible in Python
Use Python’s synchronous, multi-threading, queue, and asyncio event loop to make 100 HTTP requests and see which solution performs the best. It is easy to send a single HTTP request by using the requests package. What if I want to send hundreds or even millions of HTTP requests asynchronously? This article is an exploring note to find my fastest way to send HTTP requests. The code is running in a (…)
Data scientist’s guide to efficient coding in Python
Tips and tricks I use for writing clean codes on a day-to-day basis
Visualization and Interactive Dashboard in Python
My favorite Python Viz tools — HoloViz Image from datashader.org with permission It is surprising to me that many data scientists do not know HoloViz . HoloViz is my favorite Python viz ecosystem, which comprises seven Python libraries — Panel, hvPlot, HoloViews, GeoViews, Datashader, Param, and Colorcet. Why do I love Holoviz? HoloViz allows users to build Python visualization and interactive (…)
Styling Excel Cells with OpenPyXL and Python
OpenPyXL gives you the ability to style your cells in many different ways. Styling cells will give your spreadsheets pizazz! Your spreadsheets can have some pop and zing to them that will help differentiate them from others. However, don’t go overboard! If every cell had a different font and color, your spreadsheet would look like … Styling Excel Cells with OpenPyXL and Python Read More » The (…)
Build Your First Visualizer Tool using OpenCV
ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction In today’s world, we see thousands of great products, and … The post Build Your First Visualizer Tool using OpenCV appeared first on Analytics Vidhya .
How Many Ads Have You Watched Today?
Data Science A complete time-series analysis on ads data Image by author Have you ever watched an in-game advertisement to desperately collect coins and diamonds, or to revive at a level and try again? If so, you are not alone. Some ads are OK, I mean, they need to promote their product and nailed it in doing so, but others are just straight-up annoying. If you’ve been watching enough YouTube, (…)
Run your TensorFlow job on Amazon SageMaker with a PyCharm IDE
As more machine learning (ML) workloads go into production, many organizations must bring ML workloads to market quickly and increase productivity in the ML model development lifecycle. However, the ML model development lifecycle is significantly different from an application development lifecycle. This is due in part to the amount of experimentation required before finalizing a […]
Docker based RStudio & PostgreSQL
This is part one of the two part post related to Docker, PostgreSQL databases and Anomaly data-sets. In recent LinkedIn posts ( original and Rami ’s repost ) and tweet , I asked the internet for their favorite datasets for anomaly detection problems, particularly in the time-series domain. I got lots of responses, and now have a massive amount of data to play with, thank you folks who responded. (…)
A Practical Guide to Working with Geospatial data using QGIS: Part 1
Introduction Recently, I got to work on a research project involving analyzing GeoSpatial data. To analyze such data, visualization is an extremely important step. You can see several patterns easily on a map. If the data contains 100 features, it would be nice if we could plot a map of those features and see if the data intuitively makes sense. QGIS is a nice application that allows analysis, (…)
Automate Microsoft Excel and Word Using Python
Integrate Excel with Word to generate automated reports seamlessly Continue reading on Towards Data Science »
Create synthetic time-series with anomaly signatures in Python
A simple and intuitive way to create synthetic (artificial) time-series data with customized anomalies — suited to industrial applications. Continue reading on Towards Data Science »
Kubernetes vs. Docker: What Does it Really Mean?
As common as the Kubernetes vs. Docker comparison may sound for anybody in the DevOps and container orchestration space, this phrase or… Continue reading on CloudDrove »
Fraud Detection in iGaming
MACHINE LEARNING | DATA SCIENCE | GAMING How we flag fraudulent and malicious behaviour using Machine Learning We are living in a digital world. Everything we do is powered by some digital technology, either directly or indirectly. Criminal behaviour has also gone digital. Cyber-criminals exploit technological advancements and their weaknesses to carry out illegal activity. The digitalisation of (…)
Implementing LSTM for Human Activity Recognition using Smartphone Accelerometer data
ArticleVideo Book This article was published as a part of the Data Science Blogathon Ever wondered how your smartphone … The post Implementing LSTM for Human Activity Recognition using Smartphone Accelerometer data appeared first on Analytics Vidhya .
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