Stock trading has one of the most complex and complicated dynamics in the present day world. In today’s time, multiple algorithms and researches have been produced to understand the complexity of the stocks trading. There is an increasing effort to understand the system dynamics of stock trading to predict the emergent behavior of the stock prices.

In order to predict stock prices adequately, one needs to…

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Data loss comes in all shapes and sizes, from an accidentally deleted document to a catastrophic server failure that wipes out a critical database. Modern businesses are absolutely reliant on data, and on the infrastructure they use to store, process, and access that data. The grim reality is that those systems and the people who use them are fallible. Most business owners are aware that backups are important, but few have a full disaster recovery plan in…

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Data science is probably the most popular concept nowadays. I believe that many people are looking for an entrance to get inside the industry, and I just happened to read an article that lists some great data science books that may be helpful for you. So I concluded it in this article and I’ve also given the books brief introductions, so you can choose the ones you’d like to read. Some of the data science books you can find it online, and I've given out the links. But most of them I…

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There have been many articles written and talks given over the last several years on abandoning the Enterprise Data Warehouse (EDW) in favor of an Enterprise Data Lake with some passionately promoting the idea and others just as passionately denying that this is achievable. In this article, I would like to take a more pragmatic approach to the case and try and lay down a process that enterprises should consider for a data management architecture.

The focus is on data lakes for…

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If a person wishes to relax himself, travelling is probably the best pick for most people. Choosing the right place to stay for your vocation is one of the most important parts in a travel, but how to do so may be a problem. Reading through reviews of a certain hotel may be a good choice, referring to visitors’ experience, you get to know some more specific details about the hotel, however, this method is not comprehensive enough, and reading a bunch of reviews would irritate you. Here is a…

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To start with Sentiment Analysis, what comes first to our mind is where and how we can crawl oceans of data for our analysis. Normally, web crawler or crawling from web social media should be one reasonable way to get access to the public opinion data resource. Thus, in this writing, I want to share with you about how I crawled the website using web crawler and proceeded to deal with those data for…

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Web scraping (also termed web data extraction, screen scraping, or web harvesting) is a web technique of extracting data from the web, and turning unstructured data on the web  into structured data that can stored to your local computer or a database.

The web scraping technique is implemented by web scraping software tools. These tools interacts with websites in the same way as you do when using a…

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The modern world seems really fast and dynamic with a multitude of new products being launched. Marketing agencies are making fortune by monitoring the markets and delivering reports on consumers’ opinions. For today, the feedback analysis is a separate area, let’s say a growing industry with an array of products and services. And the prices for those services are pretty exorbitant.

So, do vendors have a chance to cut down…

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There is a lot of talk now about data, big data, unstructured data etc. However, if I might be so bold, talking data first is putting the cart before the horse. Data is only valuable if it’s useful. As a data strategist and analyst, the focus of my work is on decisions not data, and it's not just me whose focus is shifting. PwC last year did a report on Big Decisions and this year CapGemini wrote a great article summarising their research and stating the case for excellence in data driven… Continue

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Curse of Dimensionality:

One of the most commonly faced problems while dealing with data analytics problem such as recommendation engines, text analytics is high-dimensional and sparse data. At many times, we face a situation where we have a large set of features and fewer data points, or we have data with very high feature vectors. In such scenarios, fitting a model to the dataset, results in lower predictive power of the model. This scenario is often termed as…

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With increasing frequency, CIOs are being asked by their senior management, “What’s our big data strategy?”  But do you really need a big data strategy?

In our view, companies should instead focus on data…

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• Gets Tweets from Twitter
• Clean the data
• Create a Word Cloud
• Create a data dictionary
• Score each tweet.

Gets Tweets from Twitter:

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Originally posted here. 

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In my previous blog I have explained about linear regression. In today’s post I will explain about logistic regression. 

        Consider a scenario where we need to predict a medical condition of a patient (HBP) ,HAVE HIGH BP or NO HIGH BP, based on some observed symptoms – Age, weight, Issmoking, Systolic value, Diastolic value, RACE, etc.. In this…

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To improve decision outcomes and operational performance, financial markets firms are incorporating new technologies such as advanced analytics to speed trends analysis and behavior pattern recognition in ever-larger data sets, including big data.  The new technologies apply not only to investment risk and return management, but also to…

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