Friday, May 8, 2015

Data Science with Python


At the last Tech Talk Tuesday we took an overview of Python's  Data Science related packages.







The key packages for numerical computing are Numpy, Scipy and Scikit-learn.  The documentation for python is great, and makes presentations like this easy.  These packages are loaded with code samples, even for complex concepts like  Grid search and cross validation.    The machine learning package, scikit-learn also has exercises below the code samples.  Doing the exercises enforces the concepts, and is great preparation for solving problems like the ones in Kaggle competitions.







We also demoed iPython Notebooks, a fantastic way to create live data analysis documents.




6 comments:

Mohana M said...

Excellent Sharing. Want to become a Data scientist learn Data Science with R Training | Data Science with Python Training at GangBoard. SAS Training

Mohana M said...

Excellent Sharing. You have done great job. I gathered lots of new information. . Devops Online Training | Data Science Online Training

Logavani G said...

really informative post. thank you for sharing this blog.
java training in chennai

Logavani G said...

This is seriously good, you have really highlighted some of the great points one should know. Awesome work
Wonderful suggestions and guidance
selenium training in chennai

isabellaJoseph said...

Great post.Proudly saying I’m getting fruitfulness out of what you write and share. Thank you so much for sharing.If you want to improve your Knowledge..
Dot Net Training in Chennai
Hadoop Training in Chennai
Selenium Training in Chennai
Android Training in Chennai

for IT the said...

I am technology Enthusiast. Your blog is really awesome, attractive and impressive. I like the way you think. it is very useful for Java SE & Java EE Learners. Your article adds best knowledge to our Java Online Training in India. or learn thru Java Online Training in India Students. or learn thru JavaScript Online Training in India. Appreciating the persistence you put into your blog and detailed information you provide. Kindly keep blogging.

Popular Articles