Ugonna

Intern/Lab Work

Acquired knowledge in vectors and matrices, calculus, descriptive statistics and Python.. Developed skills in assessing dataset quality, generating visualisations, and conducting hypothesis tests on data.. Gained experience in querying databases using SQL.. Learned about regression analysis using the Scikit-learn Python library and how to identify and address overfitting.. Learned how to implement logistic regression, support vector machines, and Naive Bayes classification algorithms.. Explored unsupervised learning for uncovering patterns within datasets, including the application of clustering algorithms and dimension reduction.. Discovered how to use and interpret decision trees in machine learning.. Explored how ensemble methods like random forests, boosting, and stacking enhance machine learning models.. Learned about regular expressions, manipulating text, feature engineering and text classification.. Learned about artificial intelligence, exploring reinforcement learning and the application of deep learning neural networks using the Keras Python library.. Learned about cloud computing technologies such as Amazon Web Services and Google Colab and how to deploy a machine learning algorithm.