Advanced Python and Data Science

1 Reviews

Begur Road, Bangalore

Course ID: 42226

Begur Road, Bangalore

Students Interested 0 (Seats Left 0)

1 Reviews

Date and Time

Not decided yet.

Saswat Mohanty picture
Saswat Mohanty

M.Tech

3 Years of Experience

About Saswat Mohanty

Hands on Trainings which would be very beneficial to scale up to industry requirements.
A

Ananya

Attended Advanced Python and Data Science

I joined him for Python training advance, and it was great. He gave more practical exposure and problem statements, which helped me in building project more efficiently. Also currently I am pursuing my data science and AWS under him. As I am from networking background he helped me build my competency in python and Django more on networking program side. Highly recommend Saswat sir.

About the Course

Advanced Python and Data Science


The course includes thorough coverage of Learning Algorithms, Terminology, Data Types, Data Visualization. The course takes a practical approach to creating and organizing Linear Regression ,Binary Classification ,Multiclass Classification.


Attendees will learn how to use Python to create scripts that do Linear Regression , Binary Classification, Multiclass Classification, Data Visualization - Linear, Log, Quadratic and More.


Comprehensive hands on exercises are integrated throughout to reinforce learning and develop real competency.


Students Will Learn


Linear Regression, Linear Model, Squared Error Loss Function, Stochastic Gradient Descent


Linear Regression for complex shapes, AWS - Linear Regression Models


How to evaluate regression model accuracy ,Evaluate predictive quality of the trained model, Review Default Recipe Settings Used To Train model ,Train Model With Custom Recipe and Review Performance


Adding Features To Improve Model


Normalization, Impact of Features With Different Magnitude, Normalization to smoothen magnitude differences, Train Model With Feature Normalizaton


Adding Complex Features, Logistic Regression, Binary Classification - Logistic Regression, Loss Function, Optimization, Binary Classification Approach, True Positive, True Negative, False Positive and False Negative


Data Transformation using Recipes, Text Transformation, Numeric Transformation - Quantile Binning, Numeric Transformation รข?? Normalization, Cartesian Product Transformation - Categorical and Text


Hyper Parameters, Model Optimization and Lifecycle, Data Rearrangement, Maximum Model Size, Passes, Shuffle Type, Regularization, Learning Rate, Regularization Effect

Reviews (1) See all Reviews

A

Ananya

Attended Advanced Python and Data Science

I joined him for Python training advance, and it was great. He gave more practical exposure and problem...

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Students Interested 0 (Seats Left 0)

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