Professional Overview
Machine Learning, Natural Language Processing (NLP), Data Science, Data Engineering, Computer Vision, Deep Learning, OpenCV, Convolutional Neural Networks (CNN), Artificial Intelligence (AI), PySparkRL, NLP, NLU, LLMs, KNN, k-means, agglomerative clustering, linear classifiers, SVM/kernel methods, LDA, TFIDF, BERT, GPT3/3.5/4, Fasttext, Lngchain, CNN(residual-1dCNN), RNN(nmt, bidaf, seq2seq), ontology, finite automata(task completion), python, JavaScript, C++, SQL, PySpark, pandas, Tabular, scala, Kafka, polars, nltk, Gensim, spacy, Fasttext, scikit-learn, Scipy, word2vec, glove, Tensorflow, Keras, Pytorch, Statistics, Matlab, Yolo, maskRCNN, GANs, OpenCV, ultrasound sensors, IR sensors, Google Cloud Platform tools, docker, Kubernetes, AWS
Areas of Expertise
AI & Machine Learning Engineers
Design, train, and ship production ML models — from data pipelines to model inference at scale. Covers supervised learning, neural networks, LLM integration, and model optimisation.
