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: www.anaconda.com/download/#macos.

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*Agenda:

10:00 AM - 12:00 PM : Linear regression with Regularization

12:00 PM - 2:00 PM : Logistic regression

2:00 PM - 4:00 PM : Boosting

4:00 PM - 6:00 PM : Clustering

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* Session #1:

Topic: Linear regression with Regularization

Instructor: Ankit Gehlot, Data Scientist at STYFI

LinkedIn: https://www.linkedin.com/in/ankitgehlot/

Learning Outcomes: Understand intuitively the concept of Linear Regression, how to implement it and how regularization helps in improving our regression model.

Key Takeaways:

1. Intutition behind Linear Regression
2. Implementation of Linear Regression using sklearn
3. Intuition behind Regularization and its implementation

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*Session #2:

Topic: Logistic regression

Instructor: Suryaprakash Singh, Data Scientist at TIAA

LinkedIn: https://www.linkedin.com/in/suryaprakash-singh-4b896520/

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

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*Session #3

Topic: Boosting

Instructor: Ambarish Chatterjee, Senior Manager - Analytics & Research at Kotak Life

LinkedIn: https://www.linkedin.com/in/ambarish-chatterjee-8a9a3a43/

Learning Outcomes: Understand the intuition behind Boosting and it's advantages over the other ensemble methods.

Key Takeaways:
1. Intuition behind Boosting
2. Working of Boosting Models
3. Understanding of different types of Boosting
4. Implementation of Boosting using Sklearn and XGBoost

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*Session #4

Topic: Clustering

Instructor: Nimish Ronghe, Data Scientist at Prudential Global Services Private Limited

LinkedIn: https://www.linkedin.com/in/nimish-ronghe-9576999b/

Learning Outcome: Understand the concept of unsupervised learning and how to implement it using clustering

Key Takeaway:-

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

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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!!