A Data Science Central Community

Both R & Python should be measured based on their effectiveness in advanced analytics & data science. Initially, as a new comer in data science field we spend good amount of time to understand the pros and cons of these two. I too carried out this study solely for “self” to decide which tool should i pick to get in depth of data science. Eventually, i have started realizing that both (R & Python) has its space of mastery along with their broad support to data science. Here some…

ContinueAdded by Manish Bhoge on February 7, 2014 at 11:22pm — No Comments

The term "Data Science" has been evolving not only as a niche skill but as a niche process as well. It is interesting to study "how" the Big data analytics/Data Science/Analytics can be efficiently implemented into the enterprise. So, along with my typical study of analytics viz. Big data analytics I have been also exploring the methodologies to bring the term "Data Science" into mainstream of existing enterprise data analysis, which we conventionally know as "Datawarehouse & BI". This…

ContinueAdded by Manish Bhoge on December 12, 2013 at 9:30am — 1 Comment

Practicing Data science…

Added by Manish Bhoge on October 18, 2013 at 12:22pm — No Comments

Text (word) analysis and tokenized text modeling always give a chill air around ears, specially when you are new to machine learning. Thanks to Python and its extended libraries for its warm support around text analytics and machine learning. Scikit-learn is a savior and excellent support in text processing when you also understand some of the concept like "Bag of word", "Clustering" and "vectorization". Vectorization is must-to-know technique for all machine leaning learners, text miner…

ContinueAdded by Manish Bhoge on September 25, 2013 at 12:30pm — No Comments

Data analysis echo system has grown all the way from SQL's to NoSQL and from Excel analysis to Visualization. Today, we are in scarceness of the resources to process ALL (You better understand what i mean by **ALL**) kind of data that is coming to enterprise. Data goes through profiling, formatting, munging or cleansing, pruning, transformation steps to analytics and predictive modeling. Interestingly, there is no one tool proved to be an effective solution to run…

Added by Manish Bhoge on August 27, 2013 at 11:00am — 1 Comment

Most of Datawarehouse folks are very much accustomed with the term "Capacity Planning", Read Inmon. This is widely used process for DBA's and Datawarehouse Architects. In an typical project of data management and warehouse wide variety of audience is involved to drive the capacity planning. It involves everyone from Business Analyst to Architect to…

ContinueAdded by Manish Bhoge on February 15, 2013 at 2:46am — No Comments

There are lots of topics floating around in the space of data analysis like statistical modeling, predictive modeling. There have always been questions in mind which technique to choose? which is preferred way for data analysis? Some articles and lecture highlight machine learning or mathematical model over statistics modeling limitations. They mention mathematical modeling as a next step of accuracy and prediction. This kind of articles create more questions in mind of naive…

ContinueAdded by Manish Bhoge on February 12, 2013 at 12:26am — No Comments

It has been while when Big data entered into the market and buzz the analytics world. Now a day all analytics leaders are chanting about Big data applications. Since I have started with Hadoop technologies and with Machine learning one question has been bugging in mind:

**Which is a greater innovation Big Data Or Machine Learning…**

Added by Manish Bhoge on May 13, 2012 at 11:50pm — 1 Comment

- (R + Python)
- Operational Data Science: excerpt from 2 great articles
- Warm-up exercise before data science.
- Python Scikit-learn to simplify Machine learning : { Bag of words } To [ TF-IDF ]
- An indispensable Python : Data sourcing to Data science.
- Big Data : How do you run capacity planning ?
- Data analysis beginners

© 2021 TechTarget, Inc. Powered by

Badges | Report an Issue | Privacy Policy | Terms of Service

**Most Popular Content on DSC**

To not miss this type of content in the future, subscribe to our newsletter.

- Book: Applied Stochastic Processes
- Long-range Correlations in Time Series: Modeling, Testing, Case Study
- How to Automatically Determine the Number of Clusters in your Data
- New Machine Learning Cheat Sheet | Old one
- Confidence Intervals Without Pain - With Resampling
- Advanced Machine Learning with Basic Excel
- New Perspectives on Statistical Distributions and Deep Learning
- Fascinating New Results in the Theory of Randomness
- Fast Combinatorial Feature Selection

**Other popular resources**

- Comprehensive Repository of Data Science and ML Resources
- Statistical Concepts Explained in Simple English
- Machine Learning Concepts Explained in One Picture
- 100 Data Science Interview Questions and Answers
- Cheat Sheets | Curated Articles | Search | Jobs | Courses
- Post a Blog | Forum Questions | Books | Salaries | News

**Archives:** 2008-2014 |
2015-2016 |
2017-2019 |
Book 1 |
Book 2 |
More

**Most popular articles**

- Free Book and Resources for DSC Members
- New Perspectives on Statistical Distributions and Deep Learning
- Time series, Growth Modeling and Data Science Wizardy
- Statistical Concepts Explained in Simple English
- Machine Learning Concepts Explained in One Picture
- Comprehensive Repository of Data Science and ML Resources
- Advanced Machine Learning with Basic Excel
- Difference between ML, Data Science, AI, Deep Learning, and Statistics
- Selected Business Analytics, Data Science and ML articles
- How to Automatically Determine the Number of Clusters in your Data
- Fascinating New Results in the Theory of Randomness
- Hire a Data Scientist | Search DSC | Find a Job
- Post a Blog | Forum Questions