Life of a startup guy in India

  1. Sometimes VC money is like BC money
  2. we can build Taj Mahal in excel
  3. angel investors all died and went to heaven where they are watching Indra and Maneka
  4. devil is in details of everything they asked you to just sign saying, arrey yaar, this is a standard form
  5. hiring is always just in time
  6. zuckerberg is the 10th avatar of vishnu
  7. a million dollars is not cool. A billion dollars is cool. A billion people is even hotter
  8. lying is number 3 sport after cricket and politics discussion
  9. everybody criticizes anything
  10. steve jobs came to india as a teenager. So Indians can claim credit
  11. every indian american who got succesful is because of his Indian DNA as per our newpapers
  12. everybody knows anybody. Or says they do
  13. every developer can learn hadoop in 2 days just payment in advance
  14. every client’s cheque is delayed atleast once
  15. Dilbert was a graduate from IIT
  16. In india there is no ration on passion, but often we have passion for ration

How do you pick a modeling method? Spotlighted PAW session

Michael Berry whom we interviewed here at is giving a session at PAW on Modeling Techniques

This is a featured post by our sponsor-

Spotlighted PAW Session: Michael Berry on Modeling Techniques

A long-term veteran expert, consultant, and instructor – who is normally found in a keynote session – TripAdvisor’s Michael Berry will serve PAW’s audience with invaluable insights by way of his highly rated, captivating speaking style. Mr. Berry is also the founder of the consultancy Data Miners and co-author of popular books, including Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management.

Witness this and 30 other sessions at Predictive Analytics World for Business,

September 27- October 1, 2015 in Boston.

Michael Berry Analytics Director

Tripadvisor for Business

SESSION: Picking the Right Modeling Technique for the Problem

Decision Tree? Neural Network? Regression? Naive Bayes? Support Vector Machine? It is said that when your only tool is a hammer, every problem looks like a thumb. Modern data mining toolkits are full of tools, but how do you pick the right tool for a particular predictive analytics task? Presenter: Michael Berry

Ten Thoughts on giving Analytics Trainings

I have delivered trainings by now to hundreds of students and professionals by both online as well as offline means.  Mostly I get great reviews. But twice in a decade I have bombed too.


Here are some thoughts on this-

1) Prior preparation is very necessary. day before class , whole code should be run one day before and tested.
Why do trainers not prepare every time- well time bandwidth is an issue.

2) Enterprise  clients spend on invoice, infrastructure, transport but also on per employee time. So errors during a training session with retail clients it is ok, but one has to be be very prepared with corporate clients. Corporate clients do not tolerate errors of even ten minutes.

3) You can lose the flow if you interrupt your training to questions and answers. Sometimes it is best to park questions.

4) Self discipline is always necessary in case a few assertive students don’t corner or hijack the agenda to what they need . The needs of the many outweigh the needs of the few in analytics training.

5) Even after numerous prior meetings, client requirements and intentions can remain unclear on what they want from training. Keep some flexibility but maintain pedagogy discipline.

6) Always ask prior requirements to read or join the training.

7) Homework rarely works with adults taking training in both online or offline classes. Classroom quizzes and live tasks work better.

8) R and Python are very dynamic in analytics technology. So keep updating those ppts. Sharing 10% of your content for free online can bring you a lot of leads for repeat business free.

9) Always ask for due time to create, rehearse and present the training regardless of client urgency. Training in analytics are long term investments and hurry can compromise your quality and reputation.

10) Always be proactive. If client is very unhappy, be the first to offer discounts. If the client is happy ask for a LinkedIn testimonial.