Visualization for Timeseries Exchange Data

Recently, I had the opportunity to deal with crypto exchange public data and this allowed me to visually explore the data using Plotly libraries, one of the best visualization tools available, as it will enable us to have general interactive graphs without worrying about coding part — like I used to do with Bokeh. If … Read more

The probabilities implied by bookmaker odds: Introducing the ‘implied’ package

[This article was first published on R – opisthokonta.net, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don’t. My package for converting bookmaker odds into probabilities is now on … Read more

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R tips and tricks – Paste a plot from R to a word file

[This article was first published on R – Eran Raviv, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don’t. In this post you will learn how to properly paste … Read more

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Using R: 10 years with R

Yesterday, 29 Feburary 2020, was the 20th anniversary of the release R 1.0.0. Jozef Hajnala’s blog has a cute anniversary post with some trivia. I realised that it is also (not to the day, but to the year) my R anniversary. I started using R in 2010, during my MSc project in Linköping. Daniel Nätt, … Read more

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Create Your First Chatbot!

Image by Lukáš Skucius from Pixabay Whether you’re a data scientist, data analyst, or software engineer; and whether you have a strong handle on NLP tools and approaches, if you’re here, you’ve likely wondered how a chatbot works and how to build one, but haven’t ever had the need or chance. Well… you’re here now, … Read more

How to Create a Correlation Matrix with Too Many Variables in R

Efficiently filter out uncorrelated variables to see more relevant results. I used the Kaggle House Prices Dataset which has 79 explanatory variables. In my analysis, I tried to look at correlations between all of the variables and realized there are just too many variables to make sense of any typical visual aid. I tried several … Read more

Do You Really Need Trash Cans?

Predicting The Next Pitch with Machine Learning The 2019–2020 MLB off-season was dominated by the revelation that the Houston Astros stole opposing pitcher’s signs during their 2017 World Series-winning season. This was accomplished by looking at a live camera feed from center field in an area just off the dugout and communicating the next pitch … Read more

States, Actions, Rewards — The Intuition behind Reinforcement Learning

What exactly is reinforcement learning, and how does an RL algorithm work in practice? In 2014, Google acquired a British startup named DeepMind for half a billion dollars. A steep price, but the investment seems to have paid off many times over just from the publicity that DeepMind generates. ML researchers know DeepMind for its … Read more

Using CTEs to Improve SQL Queries

As mentioned early CTEs are temporary tables created in a query, which are referenced later. Here is the basic layout of a CTE. WITH CTE_NAME(column_1, column_2, column_3)AS(–normal SQl querySELECT *FROM table) In the code above, the CTE must start with a WITH. This tells your query that it is a CTE statement. Next, CTE_NAME is … Read more

Go highly accurate or go home?

Photo by Jamie Street on Unsplash What we can learn from data science projects that don’t give us great prediction results: time series forecasting with bike sharing data Scrolling through notebooks on kaggle or reading those data science project stories where people get highly accurate results that perfectly solve the underlying business problem can be … Read more

Understanding Probability And Statistics: The Essentials Of Probability For Data Scientists

Explaining The Key Concepts Of Probability For Statisticians The field of data science revolves around probability and statistics. Hence, it is crucial to have a solid understanding of these concepts. This article intends to explain the essentials of probability. I will be writing a number of articles on the subject of probability and statistics. They … Read more

Can we perform NLP on unfamiliar (natural) languages?

As I don’t know how Bulgarian grammar work or even many basic words, I will try to explore the dataset (Krisko’s lyrics) without doing any preprocessing. First, I will check what are the words used frequently in his songs. import io# Read the datawith io.open(‘/resources/data/krisko_lyrics.txt’, encoding=’utf-8′) as f:krisko_text = f.read().lower().replace(‘\n’, ‘ \n ‘)# Split into … Read more

DIY dashboard for Coronavirus In

Step 4. Initialize Heroku, add files to Git, and deploy $ heroku create my-dash-app # change my-dash-app to a unique name$ git add . # add all files to git$ git commit -m ‘Initial app boilerplate’$ git push heroku master # deploy code to heroku$ heroku ps:scale web=1 # run the app with a 1 … Read more

Predicting the misclassification cost incurred in air pressure system failure in heavy vehicles

[This article was first published on Stories Data Speak, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don’t. Abstract The Air Pressure System (APS) is a type of function … Read more

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SR2 Chapter 2 Hard

[This article was first published on Brian Callander, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don’t. Here’s my solution to the hard exercises in chapter 2 of McElreath’s … Read more

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