Do you enjoy statistics and programming? Are you currently studying math and statistical learning (such as machine learning)? Are you excited to learn the latest technologies and techniques in data science? If your answers are more than just one yes, your career path may take you to data analysis very soon. Many students in programming and statistics can find a very remunerative career in data science, as it is an ever-growing field with a lot of potential. But right from the start, you have to ask yourself how you are going to approach this discipline and how you are going to tackle the programming challenges ahead of you. And here comes the question that all data scientists had to answer at the very beginning of their careers: should I learn Python or R programming to start working on data analysis? This is a tough question since Python and R are both versatile programming languages in data statistics. They were born in the same period (the late 80s or the start of the 90s) and bot
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An Overview of Agent Based Intelligent Systems and Its Tools
In an Artificial Intelligence world, Agent-based technology is one of the most vibrant and important areas of R&D, emerging in Information Technology in the industry in recent years. Intelligent Agent (IA) is an autonomous entity which observes, analyses and responds to an environment appropriate to achieve the expected objective. The IA posses several categories such as Coordination, Integration,
Utilization of Data Mining in Human Resources
Role of Data Mining in HR activities. Data mining is the act of analyzing huge informational indexes so as to create new data. In human resources (HR), Data mining is a fundamental device so as to contend with the quickly developing challenge, for example, computerized reasoning and the technological headway of robotized programs.
Big data is everywhere. Making good use of big data analysis will improve the quality of work.
Statistical Methods Research
DSF: Rohan is a new member of the Data Science Foundation and has asked for our members to support the research he is doing for his MSc thesis. I am sure we can help by participating in his survey and sharing our opinions… For my thesis I am researching various statistical methods and their ability to deliver value for predictive modelling; more specifically ‘churn prediction’. To compare the various models in a complete and honest way I want to evaluate the models based on six performance characteristics.
Thank you to everyone that has filled in the survey or shared my request! 35 valuable opinions have been gathered; 22 came from a corporate environment and 13 are from researchers and academics. I will now close down the survey. Thanks again for your help!
Bias in Machine Learning
Bias and variance are two major issues we try to manage in machine learning. We are always looking for a trade-off between the two. Bias has to do with the training data while variance has to do with the model output.
Good to know about this. Thanks, Chris, for bringing it up. I like to have more details so that the methodology can be applied in our day-to-day machine learning endeavours.
HG Insights Fuels Precision Marketing and Sales Programs at Scale with Marketo Engage
Santa Barbara, CA, May 23, 2019 -- HG Insights, a global leader in technology intelligence, announced today the release of HG for Marketo, which helps businesses instantly personalize conversations, prioritize prospects, and accelerate revenue with technographics.
Promotion of advanced technology requires training of target customers to enable them to understand technology, preferably with examples.
Machine Learning with Python by Ajit Singh
Machine learning can be described as a form of statistical analysis, often even utilizing well-known and familiar techniques, that has bit of a different focus than traditional analytical practice in applied disciplines. The key notion is that flexible, automatic approaches are used to detect patterns within the data, with a primary focus on making predictions on future data.
Thank you all for your support and cooperation.Regards,Ajit Singh
International Data Science Awards Live and Entry Pages Open
The entry pages for the International Data Science Awards are now live and entries are being accepted. The awards were launched at the AI & Big Data Expo held at Olympia, London on 25 April. Entry pages will remain open until September with judging taking place in October.
Its now time to start thinking about the project you will enter into the International Data Science Awards. The Support of the Chartered Institute of Public Relations will really help to raise the profile of the awards and generate interest in the participants
Big Data Business Ecosystem
A business ecosystem, first defined by James F Moore, is “An economic community supported by a foundation of interacting organizations and individuals. In this regard, an ecosystem does not yet exist in Europe for Big Data. However, from at least one perspective a Big Data ecosystem (removal of ‘business’ is deliberate) does exist in many industries in a very simple form.
Request you all to please share your valuable and experienced suggestions...