• Provided assistance to learners, addressing queries on diverse data science and machine learning topics• Assessed learners' data science projects, offering feedback and guidance for improvement• Developed two projects—sentence generation using N grams and recommendation systems—and delivered step-by-step explanations• Created engaging questions on machine learning topics, including linear and logistic regression

• Developed new Topic Modelling approach to identify Social Networks for Customer segmentation• Leveraged RoBERTa, to identify negative sentiment tweets from large-scale Twitter data• Employed LDA to uncover topics within the negative tweets providing valuable insights into customer concerns• Transformed tweet into vector embeddings based on the identified topics for social network construction• Applied modularity clustering to reveal customer segments for targeted service improvement initiatives

• Developed a Neural Network Observer for Position and Speed Estimation in vector control for PMSM • Automated the whole data collection process for neural network using MATLAB and Simulink together• Implemented a Feed Forward and Auto-Regressive model and final MSE value achieved was 3.06e-05• Finally able to do a 1 on 1 interchange of Neural Network observer with other sensor less technique for PMSM