This the second part of Reinforcement Learning (Q-learning). If you would like to understand the RL, Q-learning, and key terms please read Part 1.
In this part, we will implement a simple example of Q learning using the R programming language from scratch. It is expected from you to understand the basics of R programming and complete the reading of Part 1 of this article.
We are coding the algorithms using the R base package…Continue
Added by Nitin Agarwal on June 4, 2020 at 8:23pm — No Comments
Have you heard about AI learning to play computer games on their own and giving tough competitions to expert Human gamers?
A very popular example being Deepmind whose AlphaGo program defeated the South Korean Go world champion in 2016. Other than this there are other AI agents developed with the intent of playing Atari games like…Continue
Added by Nitin Agarwal on June 4, 2020 at 7:51pm — No Comments
Added by Janardhanan PS on February 10, 2020 at 7:14pm — No Comments
Quite often, non-technical executives have difficulties understanding what programming, on a very fundamental level, is all about. Because of that knowledge-gap, they tend to hire and overburden experienced data professionals with tasks which they are hopelessly overqualified for. Such as, for example, doing ad-hoc SQL queries on CRM data: "You're the go-to-guy for all things data, and we need the results for the board meeting tomorrow." That's a quite humbling and frustrating…Continue
Added by Rafael Knuth on December 5, 2019 at 6:30am — No Comments
Nowadays, most data scientists use either Python or R as their main programming language. That was also my case until I met Julia earlier this year. Julia promises performance comparable to statically typed compiled languages (like C) while keeping the rapid development features of interpreted languages (like Python, R or Matlab). This performance is achieved by just-in-time (JIT) compilation. Instead of interpreting code, Julia compiles code in runtime. While JIT compilation has…Continue
Added by Daniel Moura on August 22, 2019 at 1:00pm — No Comments
One can seriously argue about what programming language is the best for data analysis, but there is one universal metric that can define your choice: speed of calculations. Therefore, the word "best" in the title means the languages that lead to most performant applications. If most performant program can also be written in an easy-to-use, easy-to-learn, dynamically-typed…
Added by jwork.ORG on January 26, 2019 at 2:54pm — No Comments
The following advice is built from my experience working as a data scientist on a variety of projects across different data & engineering teams. Many data scientists (myself included) do not come from a computer science or software development background, so may not have formal training or good habits in code writing. These tips should help data scientists work collaboratively to write good code and build models in a way that will be easier to…Continue
Added by Jason Byrne on March 2, 2018 at 3:00am — No Comments
If you have ever wondered or still wonder what the best job in Silicon Valley is, which ranks No. 1 on Glassdoor’s best jobs in America list for 2016 and 2017, you can stop now. Also referred to as the sexiest job of the 21st century, it’s data science.
Whether you look at the salary and packages currently being offered for this job, or the rise in demand for these professionals, the numbers still look pretty impressive. According to Glassdoor, data scientists make on average $128,549…Continue
Added by Claudia Virlanuta on February 13, 2018 at 9:30am — No Comments
This paper enlightens the way companies can design Intelligent System to understand their customers’ sentiments better to improve their experience, which will help the businesses change their market position.
Sentiment analysis is widely acknowledged in the web and social media monitoring. It allows businesses to gain a comprehensive public opinion on the organization and its services. The ability to deduce insights from the text and emoticons from social media is a…Continue
Added by Valiance Solutions on December 20, 2017 at 1:30am — No Comments
This is a tutorial to show how to implement dashboards in R, using the new "flexdashboard" library package.
this new library leverages these libraries and allows us to create some stunning dashboards, using interactive graphs and text. What I loved the most, was the “storyboard” feature that allows me to present content in Tableau-style frames. Please note that for this you need to create RMarkdown (.Rmd) files and insert the code using the…Continue
About a month ago in a blog, I introduced what I described as a “spectral attenuation monitor.” At the time I only had an image from MS Works that…Continue
Added by Don Philip Faithful on April 9, 2017 at 6:30am — No Comments
In order to prevent my programs from freezing up while running long calculations, I generally run the calculations on separate threads. In Java, this process can be accomplished by separating the GUI from processing. In the code below, a thread for an instance of MyProcessing would be invoked using start(): e.g. “(new MyProcessing()).start();” would run indefinitely until T is made null. T can be made null by calling stop() or by directly making T null. Often when the GUI is closing, I…Continue
Added by Don Philip Faithful on March 25, 2017 at 9:42am — No Comments
Last Sunday at Trivadis Tech Event, I talked about R for Hackers. It was the first session slot on Sunday morning, it was a crazy, nerdy topic, and yet there were, like, 30 people attending! An emphatic thank you to everyone who came!
R a crazy, nerdy topic, - why that, you'll be asking? What's so nerdy about using R?
Well, it was about R. But it was neither an introduction ("how to get things done quickly with R"), nor was it even about data science. True, you…
Added by Sigrid Keydana on March 24, 2017 at 2:30am — No Comments
The post 'Top programming languages that will be most popular in 2017' was originally posted on the HackerEarth blog.
Which is the most preferred programming language or the top programming languages to learn across the globe? How do we judge it and what should be the criteria?
'By most preferred language, we do…Continue
Probably like most people, I tend to recognize data as a stream of values. Notice that I use the term values rather than numbers although in practice I guess that values are usually numerical. A data-logger gathering one type of data would result in data all of a particular type. Perhaps the concept of “big data” surrounds this preconception of data of type except that there are much larger amounts. Consider an element of value in symbolic terms, which I present below: there is an index such…Continue
Added by Don Philip Faithful on December 10, 2016 at 9:30am — No Comments
This post covers the following tasks using R programming:
This blog contains some snippets of code that I tend to use in Java. I acknowledge that somebody else writing this blog might include different code. Except for a short course at Sun Educational Services, most of my Java programming skills are self-taught. I’m unsure if people with formal backgrounds in computer science might have different styles and conventions. Mine have been shaped primarily by my needs.
Creating a Graphical User Interface…Continue
Added by Don Philip Faithful on November 6, 2016 at 8:00am — No Comments
As part of Data Science tutorial Series in my previous post I posted on basic data types in R. I have kept the tutorial very simple so that beginners of R programming may takeoff immediately.
Please find the online R editor at the end of the post so that you can execute the code on the page itself.
In this section we learn about control structures loops used…
Added by dataperspective on May 18, 2016 at 8:30pm — No Comments
The 10th International Web Rule Symposium (RuleML) 2016 Call for Papers
Stony Brook, NY, 6-9 July, 2016
* Best papers of RuleML 2016 will be invited to submit a revised and extended version to the "Rapid Publications" category of the journal TPLP (Theory and Practice of Logic Programming).
* Best papers of RuleML 2016…
Added by Ольга Сушкова on March 16, 2016 at 1:34am — No Comments
For many scientists and data analysts, outliers are like a ‘black box’ in conventional statistics. Many believe that these outlier observations arise due to errors or due to improper procedures in the experiment. Majority of them eliminate the outliers unscientifically by brute force. Some identify them statistically but discard them as if they are junk. Some understand importance of the outliers but they do not know how to deal with it. If you are one among them or interested in scope of…Continue
Added by Venu Perla PhD on November 1, 2015 at 4:45pm — No Comments