Learn how to perform different dimensionality reduction using feature extraction methods such as PCA, KernelPCA, Truncated SVD, and more using Scikit-learn library in Python.
Learn how to make a simple math quiz game in Python utilizing the PyInputPlus module to verify the user input.
Learn the importance of dropout regularization and how to apply it in PyTorch Deep learning framework in Python.
Learn how you can perform named entity recognition using HuggingFace Transformers and spaCy libraries in Python.
Learn how to perform logistic regression algorithm using the PyTorch deep learning framework on a customer churn example dataset in Python.
Learn how to create a CRUD application as a RESTful API using Flask and SQLAlchemy, making a Bookshop web application as a demonstration in Python.
Learn how to handle one of the main data science common problems, which are imbalanced datasets, how to deal with them using SMOTE, tweaking class weights, and resampling in Python.
Learn how you can make a DHCP listener by sniffing DHCP packets in the network using the Scapy library in Python.
Build a recommender system for market basket analysis With association rule mining with the Online Retail dataset in Python.
Learn how to perform data analysis and make predictive models to predict customer churn effectively in Python using sklearn, seaborn and more.
Learn how you can make interactive HTML tables with pagination, sorting and searching just from a pandas dataframe using pandas and jQuery data tables in Python.
Learn how to build a model that is able to detect fraudulent credit card transactions with high accuracy, recall and F1 score using Scikit-learn in Python.
Learn how you can inject Javascript, HTML or CSS to HTTP response packets in a spoofed network using Scapy and NetfilterQueue in Python.
Exploring the fake news dataset, performing data analysis such as word clouds and ngrams, and fine-tuning BERT transformer to build a fake news detector in Python using transformers library.
Learn how you to make a MAC address changer in Windows and Linux using the subprocess module in Python.
Learn how you can extract Google Trends Data such as interest by region, suggested searches, and more using pytrends unofficial library in Python.