Credit card fraud analysis using Data science


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About this session

Great Learning brings you this live session on ' Credit card fraud analysis using Data science'. In this session, you will be working on an end-to-end case study to understand the different stages of Model building using the Machine Learning concept. This will deal with 'data manipulation' with pandas, Numpy and 'data visualization' with Matplotlib and Seaborn libraries with the credit card dataset. After Data manipulation and Data visualization, Exploratory data analysis will be performed and then an ML model will be built on the credit card dataset to create a model/system which can predict the transaction is fraud or not according to the different attributes. You will also learn about the basics of the sci-kit-learn library to implement the machine learning algorithm.

About the Speaker

Ms. Sampriti Chatterjee

Great Learning


Sampriti has been working in the field of data science and has expertise in languages such as Python, SQL, and Java. She also has expertise in the field of deep learning and has worked with deep learning frameworks such as Keras and TensorFlow 2.0. She is been in the technical content side for the last few years.

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