Batloung Morojele

In this job shadowing experience I followed a DevOp team for a day in their daily operations in:

• Streamlining software delivery, infrastructure management, and security compliance.
• Automating processes and implementing CI/CD pipelines for seamless deployments.
• Monitoring systems for performance and security, and managing vulnerabilities to meet regulatory standards.

• Proficient in designing and implementing predictive models using Python, leveraging libraries such as Scikit-learn, TensorFlow, and Keras to develop supervised and unsupervised learning algorithms. Skilled in training models on large datasets and optimizing their performance through advanced enhancement techniques.
• Experienced in configuring and deploying neural networks, including multilayer perceptron's, for multi-class image classification tasks, ensuring high accuracy and efficient performance through careful model architecture design and parameter tuning.
• Demonstrated capability in applying transfer learning methodologies, particularly utilizing MobileNet-V2, to accelerate model training and improve classification performance for image-based tasks.
• Conducted sentiment analysis on Steam game reviews to develop a recommendation system, utilizing a Recurrent Neural Network with Long Short-Term Memory (LSTM) units to predict the likelihood of a new game being positively received by the user.
• Analyzed the impact of text pre-processing techniques and training dataset size on the performance of Gaussian Naive Bayes, Support Vector Classifier, and Logistic Regression models, providing insights into optimal configurations for text-based classification tasks.
• Proficient in transforming unstructured data into structured formats, demonstrated through the compilation of a Champions League dataset for a research project. Conducted a comparative analysis of machine learning models and Bayesian networks, which involved extensive data cleaning, pre-processing, and validation to ensure the integrity of the dataset.
• Skilled in data visualization and exploratory data analysis to uncover relationships between variables, providing critical insights for feature selection and model optimization.
• Implemented robust reporting mechanisms to track progress against goals effectively.