In this hands-on project, we will build and train a simple artificial neural network model to detect spam/fake Instagram accounts. Fake and spam accounts are a major problem in social media. Many social media influencers use fake Instagram accounts to create an illusion of having so many social media followers. Fake accounts can be used to impersonate or catfish other people and be used to sell fake services/products.
In this hands-on project, we will build and train a simple artificial neural network model to detect spam/fake Instagram accounts. Fake and spam accounts are a major problem in social media. Many social media influencers use fake Instagram accounts to create an illusion of having so many social media followers. Fake accounts can be used to impersonate or catfish other people and be used to sell fake services/products.
By the end of this project, you will be able to:
- Understand the applications of Artificial Intelligence and Machine Learning techniques in the banking industry
- Understand the theory and intuition behind Deep Neural Networks
- Import key Python libraries, dataset, and perform Exploratory Data Analysis.
- Perform data visualization using Seaborn.
- Standardize the data and split them into train and test datasets.
- Build a deep learning model using Keras with Tensorflow 2.0 as a back-end.
- Assess the performance of the model and ensure its generalization using various Key Performance Indicators (KPIs).
Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
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