Building a successful career in the field of data science needs a lot more than just a thorough understanding of the various machine learning models. One has to also undergo a paradigm shift with regards to how you would typically approach any technical problems.
We will discuss how seemingly disjoint components of the digital ecosystem are working together to make data-driven decision making central to every functional aspect of every business vertical.
Workshop: Building a Scorecard using Python
Financial Scorecards are used by banking organizations to judge the financial stability of their portfolio and take business decisions.
The workshop will guide you through the EDA process using Python and will show the different kind of visualizations that can enable better data understanding.
While building this scorecard, we will demonstrate the outcomes of 3 different Machine Learning algorithms; Random Forest, Support Vector Machine and Gradient Boosting.
Workshop: Time Series analysis in Python
Time series analysis has been around for centuries helping us to solve from astronomical problems to business problems and advanced scientific research around us now. Time stores precious information, which most machine learning algorithms don’t deal with. Time series can be applied to various fields like economy forecasting, budgetary analysis, sales forecasting, census analysis and much more.
We will look at how to dive deep into time series data and make use of deep learning to make accurate predictions.