Data science, also known as data-driven decision, is an interdisciplinery field about scientific methods, process and systems to extract knowledge from data in various forms, and take descision based on this knowledge. A data scientist should not only be evaluated only on his/her knowledge on machine learning, but he/she should also have good expertise on statistics. I will try to start from very basics of data science and then slowly move to expert level. So let’s get started.
LSTM stands for Long short term memory, LSTMs came into picture to overcome the disadvantage of RNN. RNN has a disadvantage that it cann’t store long sequences.
Kibana is very popular nowdays to visualize the Elastic search data but one aspect that Kibana falls short is in time series analysis and visualization. This is precisely where Timelion comes into picture.
This tutorial is for the beginers who want to learn Elasticsearch from the scratch. In this tutorial i am gonna cover all the basic and advace stuff related to the Elasticsearch. So let’s get started.
Elasticsearch is a real-time distributed search and analytics engine. It allows you to explore your data at a speed and at a scale never before possible. It is used for full text search, structured search, analytics and all three in combination. Elastic search is an open source search engine built on top of Apache Lucecne, a full text search engine library.
Learning new things are always exciting. Today i will be sharing about Twitter sentiment analysis but first we need to get old data. Using Twitter API it is not possible to get older tweets. To get older data i am using the I’m using Jefferson utility. Clone this repository in your local machine and run below command to get 6000 tweets from 1-12-2015 to 2-12-2015 of #ChannaiFloods.
Before starting Sentiment analysis we need to prepare out text data. Following steps need to execute to clean the corpus and prepare it for the further analysis.
I have been using ggplot to plot in python but the limitation of ggplot is that it is not much interactive. Then my exploration started and i found D3.js a good alternative to plot interactive graphs. D3.js is not much famous in Data science community because it reqires knowleedge of jave script and css. Today, I am going to tell you something which will change the way you perform data visualizations in the language / tool of your choice (R, Python, MATLAB, Perl, Julia, Arduino).
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