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DataHour: Building an End-to-End Solution for Big Mart Sales Prediction

Online 06-04-2023 07:00 PM to 06-04-2023 08:00 PM
  • 7908

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  • Knowledge and Learning.

    Prizes

About the DataHour:

As the field of data science continues to evolve, it is important to make it more accessible to those who are just starting out or transitioning into this field. In this webinar, we will be taking a practical approach to building a machine-learning solution for Big Mart Sales prediction, which is a common use case in the Retail industry. We will be covering the entire data science pipeline, from

  1. Data preparation (cleaning, encoding, scaling)
  2. EDA (descriptive statistics to understand the relationship btw features)
  3. Feature Engineering (selecting most relevant features)
  4. Model Selection (selecting best algorithm)
  5. Hyperparameter Tuning (Grid Search, Randomized Search, HyperOpt)
  6. Model Deployment (using FLASK REST API and hitting API via PostMan)

The aim is to provide a hands-on learning experience for participants who are interested in learning more about data science and machine learning.


Prerequisites:
 
The zeal for learning new technologies, and good to have a basic knowledge of Machine Learning. 


Who is this DataHour for?

  • Students & Freshers who want to build a career in the Data-tech domain.
  • Working professionals who want to transition to the Data-tech domain.
  • Data science professionals who want to accelerate their career growth


Note:
E-Certificates will be provided within 24 - 48 hours of the session only to those who have attended the entire webinar. Please make sure to join the zoom webinar with your correct name and email address to ensure that your certificate is properly credited to you.


Speaker:

Bharat Sharma

Data Scientist at Fractal

Bharat Sharma is a highly skilled Data Scientist with over three years of experience in the field. He has a Master of Science degree in Data Science from LJMU UK, where his thesis focused on the application of Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) models for anomaly detection in time series data, specifically Electrocardiogram (ECG) data.

Bharat's expertise is concentrated in two key industries: Consumer Products & Goods, and Banking. He has worked on a variety of projects in these domains, ranging from customer segmentation to fraud detection and risk modelling. His analytical skills and domain knowledge have helped him deliver actionable insights to his clients and drive business value.

Connect with him on Linkedin

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