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Scala is like Python 4
Although it’s fundamentally closer to Java, Scala has clearly taken a lot of influence from Python in terms of style and functionality. As someone who has written Python code for ~7 years now, playing around with Scala feels surprisingly familiar, but it’s more akin to using a statically typed and compiled version of Python 3. Obviously, they’re very different languages, b ut if you’re an (…)
Simple Flask Pagination. Here is a simple step-by-step tutorial…
3. Modify the view to cater to pagination. ROWS_PER_PAGE = 5 @app.route(’/colors’) @login_required def colors(): # Set the pagination configuration page = request.args.get(’page’, 1, type= int ) colors = Color.query.paginate(page=page, per_page=ROWS_PER_PAGE) return render_template(’colors/all_colors.html’, colors=colors) Results are paginated using the paginate function of Flask SQLAlchemy with (…)
Streamlit Python Cool Tricks to make Your Web-Application look better
Probably you have often wondered, what can be the better ways to make your Streamlit web application shine and be user-friendly. This article covers a few easy steps, that can minimalize and tweak the already added Streamlit features within the default web application. 1. Horizontal Radio Button Default radio button widgets come in form of columns (vertically arranged). At times, we may need to (…)
What do data-driven companies have in common? Research reveals five key trends
Recent IDC research, sponsored by Tableau, found that 83% of CEOs want a data-driven organization, but only 33% of executives are comfortable questioning business KPIs and metrics1, revealing disparities between what executives “want” and “have.”(1) Nearly all executives say they want their organization to be more data-driven, but discount cultural investments that help bring that change to (…)
How To Change The Column Names Of PySpark DataFrames
Discussing 5 ways for changing column names in PySpark DataFrames Introduction In today’s short guide we will discuss 4 ways for changing the name of columns in a Spark DataFrame. Specifically, we are going to explore how to do so using: selectExpr() method withColumnRenamed() method toDF() method alias Spark Session and Spark SQL and rename one or more columns at a time. First, let’s create an (…)
Reinforcement Learning With TicTacJoe: A Simple Brain Coded Explicitly in R
Reinforcement Learning: Introduction Reinforcement Learning is a scheme of training machine learning models in which a certain agent’s actions in an environment (typically in the form of moves in a game played by the agent) are adjusted over time. Adjustments are made by reinforcing those which lead to a good outcome (reward for winning), possibly […] Article Reinforcement Learning With (…)
Introduction to TeX, LaTeX, and OverLeaf
Greetings from the academic world’s window to all of you🍂 When it comes to scholarly articles/publications, our minds surely begin to develop question marks. As a M.Sc. student, I started this job by wanting to present a successful concrete output in both my master’s thesis and the academic publication I will create. What is TeX? 📓It is a typesetting system designed, written and first released in (…)
Use Exceptions To Write Better Python Programs
How to work with exceptions and create custom ones Exceptions are usually raised when a program encounters an unexpected error. For example, if you divide by zero, or if you pass a string to a function that needed a number. But what are exceptions exactly? They are just objects, and they are all subclasses of the general Exceptionclass. The most common exceptions are: ZeroDivisionError, which is (…)
Train Your Own Chess AI
Watch your creation defeat you The best way to test our AI is to play it! Using alpha beta search, transposition tables, and few other standard chess AI techniques we can create a full chess engine to play against. The AI client was implemented in Go ( so I could use my chess lib ) and the model was hosted on a colocated python based gRPC server serving the model on Nvidia 2080 accelerated linux (…)
Predict the next word of your text using Long Short Term Memory (LSTM)
ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction: https://sm.mashable.com/t/mashable_in/photo/default/shutterstock-1208129407_trm5.960.jpg Natural language processing has been an area of research … The post Predict the next word of your text using Long Short Term Memory (LSTM) appeared first on Analytics Vidhya .
Using Fuzzy Logic for Road Traffic Congestion Index Estimation
On how to use a large set of GPS data for feeding fuzzy-based system for road traffic congestion quantification In this article, the overview of the paper “ Fuzzy Inference System for Congestion Index Estimation Based on Speed Probability Distributions ” [ 1 ] will be given. The goal is to present the paper’s findings in a more ‘readable’ way and encourage the reader to learn something new or use (…)
Building a recommendation system with Spark ML and Elasticsearch
Building a Recommendation System with Spark ML and Elasticsearch Product recommendation using Alternating Least Squares(ALS) and Cosine Similarity Image by author While working in search teams of different product companies, there was always a constant demand for building a recommendation system for users. We have build with popular search engines like Elasticsearch, SOLR, and tried perfecting (…)
Complete guide to understanding Node2Vec algorithm
An in-depth guide to understanding node2vec algorithm and its hyper-parameters Machine learning has become a vital tool in our everyday life. Almost a day doesn’t go by when you don’t use any of the wide range of applications that use machine learning in one way or another. If you have some experience with training machine learning models, you might be used to having the underlying training data (…)
Extracting Data from Excel and Outlook Files with Java
Code Implementation + Use-Cases & Situational Constraints The past 1 year plus of the Coronavirus outbreak has disrupted workplace operations on both an industrial and individual level. For me, working in the healthcare sector meant witnessing first-hand the existing cracks in the general healthcare sector. More specifically, the inefficiency in information flow & lack of a stable (…)
You Should Never Repeat Computing In Python
Image by NastasyaDay from Pixabay Built-in function tools in Python help us to cache If you do programming a lot, you must know that one programming principle is “Do Not Repeat Yourself”. That is at the coding level. We should not repeat if we can generalise. However, the topic I’m going to discuss is “Do Not Repeat Computing”. That is, if we have already calculated something, we should not (…)
Jinja + SQL = ❤️
Source: Trang Le from Pixabay Macros for maintainable, testable data analytics SQL is an analyst’s bread and butter. It’s powerful, expressive, and flexible — but the more power a language gives you, the more ways you have of shooting yourself in the foot. Better abstractions can help us with this. If we can abstract away bits of code that we use all the time, then we only have to write and (…)
Niezbalansowane dane klasyfikacyjne? Na ratunek SMOTE!
Ostatnio przygotowałem dla Was wprowadzenie czym są dane niezbalansowane i jakie wiążą się z nimi zagrożenia. W tym wpisie opiszę metodę zwaną SMOTE, którą ostatnio wykorzystałem podczas projektu w pracy. Co to jest SMOTE? Metoda SMOTE została po raz pierwszy opisana w 2002 w pracy autorstwa Nitesh Chawla zatytułowanej “SMOTE: … Artykuł Niezbalansowane dane klasyfikacyjne? Na ratunek SMOTE! (…)
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