Data Analysis Tools

As mentioned in my previous post , in this post I will be listing out the tools, blogs and forums, online courses that I have gathered over the past one year, which I felt necessary in my journey, which will be helpful to my fellow data science aspirants.
 Skillset Required:

•  Knowledge in Statistics – Exploratory analysis, doing initial analysis of the data & understanding the data to decide what techniques needs to be applied, which I feel is a must know subject. 
• Mathematics – basics of calculus, algebra etc. for mathematical formulation of the problem statement.
•  Understanding Machine learning algorithms for predictive modeling, recommendation engines, classification models, cluster analysis, social network analysis.
• Data mining skills like data cleaning/Data Munging skills, apply Machine learning techniques on the data. 
•  Visualization skills to display the results, to understand the results during building data modeling.

Tools required: 
Programming Languages: Proficiency in any two of the below mentioned languages would be advisable:

•  R 
• Python 
• Java – comes in handy when we work on Hadoop 
• C,C++

Tools required: Since I’m using Open source tools, I will be confined to them:

• R-Studio
• NLTK toolkit 
• Rapid Miner
• Weka

Important Point: 
Most of the machine learning algorithms has been already implemented as packages in the above languages/tools . We need to just download and make use of them.

Big data Tools: 

• Hadoop setup from Cloudera/Hortonworks
• Mongodb- NoSQL DB
• HBASE, PIG, HIVE.

Visualization tools: 
Though I have not explored much in this area, but till day I’m happy with R packages for visualizations.

• Data exploration in R/Python 

Few Books I have referred: 

• The Elements of Statistical Learning - 2nd Edition 
• Simon Sheather, A Modern Approach to Regression
•  Data Mining 3rd Edition by Ian H. Witten, Eibe Frank, Mark A. Hall

Online Courses: 
Though a lot of courses are available online, I have stick to very few sites as below,
For Data Analysis, Stats, Maths:

• Coursera
• Udacity
• Teachingtree
• Khan Acadamy
• Udemy 
• Statistics 

For Big Data: 

• Bigdata Univeristy 
• Cloudera
• Edureka

Blogs and forums: 
Online forums is one place where I used to get a lot of information, in Linked Groups I could get answer to all my trivial questions. You post any query and you will get elaborate answer from research scholars to industry experts, I really love this place. I will list down few Linkedin groups I follow,

• RProgramming
• R Machine Learning
• Machine Learning Connection

Blogs I follow:

• kdnuggets 
• Data Science Central 
• R-Bloggers 

Will add more when I come across the new tools. Guys hope this will serve you as a starting point for the Journey. All the best, Happy New Year. Please do add any new tools and technologies to the above list.