DataGiri's Code-along Saturdays

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Welcome to DataGiri's Code-Along Saturdays workshop. This is your opportunity to learn hands-on a wide variety of data science skills at this 8-hour workshop. In addition, to growing your skill set, you also get to network with peers and industry professionals.

The event is FREE. Please note that you are required to bring along your own laptops to participate in the workshop. Your laptop must have Anaconda 3.6 pre-installed before you begin the workshop. Find the software here:



*Details below:

Date: Saturday, 22nd June, 2019
Time: 10:00 AM - 06:00 PM
Venue: Seed Infotech, Yugay Mangal Complex-2, Gulawani Maharaj Road, Erandwane, Kothrud, Pune,[masked] (



10:00 AM - 12:00 PM : Logistic regression
12:00 PM - 2:00 PM : Support Vector Machine
2:00 PM - 4:00 PM : Clustering
4:00 PM - 6:00 PM : Ensemble Methods


* Session #1:

Topic: Logistic regression
Instructor: Ranjit Vhanamane, Data Scientist at Schlumberger
Learning Outcomes : Understand the concept of logistic regression and how to implement the same

Key Takeaways :

1. Concept of classification in ML
2. Difference between Linear and Logistic Regression
3. What is Logistic Regression
4. Cost function with gradient descent
5. Evaluation metrics
6. Implementation of logistic regression using sklearn

*Session #2:

Topic: Support Vector Machine
Instructor: Shraddha Surana, Senior Data Scientist at ThoughtWorks
Learning Outcomes : Understand the principles behind Support Vector Machines and it's usage for solving ML problems

Key Takeaways :

1. Intution behind support vectors and SVM
2. Applications of SVM in ML
3. Working of SVM
4. Implementation of SVM in Python


*Session #3

Topic : Clustering
Instructor: Yash Gandhi, Head of Data Science at Helpshift
Learning Outcomes : Understand the concept of unsupervised learning and how to implement it using clustering

Key Takeaways :

1. Understanding of unsupervised learning methods
2. Working of Clustering methods
3. Implementation of Clustering methods


*Session #4

Topic : Ensemble Methods
Instructor : Loveesh Bhatt, Data Science @ Pitney Bowes
LinkedIn :
Learning Outcome : Understand the benefits of using ensemble methods like random forests, XGBoost and how to improve your predictions with ensemble methods.

Key Takeaway :

1. What is ensembling and why it is important?
2. Averaging and voting methods
3. Bagging
4. Boosting
5. Stacking

A deep insight into Data Science by some of the top Analytics professionals in the industry followed by an hour-long networking with the leaders in Data Science, Analytics and get an opportunity to interact with leaders and your peers in our mixed format sessions. Network with the start-up Founders to see if your skills match what they are looking out for!

The workshop is FREE of cost to attend
RSVP now to reserve your spot at the event!!