Ml, Nlp, Pytorch, modern training infrastructure, Speech, Hugging Face, Llm

Deep Learning, AWS, Pytorch, Python, Kubernetes, Azure, Gcp, Nlp, Spark, Video, Llm, feature engineering, Vision, fine-tuning, cloud platforms, embeddings, training pipelines, Production Monitoring, RAG, inference, end-to-end ML systems, VLM, distributed data processing, generative AI

Apis, Tensorflow, Azure ML, Pytorch, Docker, System Design, Microsoft Azure, Kubernetes, Python, LangChain, ASR, Speech AI, Generative AI, MLflow, ML lifecycle management, Azure OpenAI, Machine learning fundamentals, TTS, CI CD pipelines, Data pipelines, Scalability and reliability

Tensorflow, Machine Learning, Python, Deployment monitoring, LLMs, Retraining, Generative AI systems, Pydantic, Drift detection, Scikit-learn, Time-series modeling, anomaly detection, Agent-based architectures, Data pipelines, Production ML systems, ML frameworks, PTorch, Feature engineering, Applied AI, Forecasting, Embeddings

Python, Machine Learning, Artificial Intelligence, REST, cloud, Tensorflow, gRPC services, MLOps tools, data pipelines

Python, Machine Learning, modern ML frameworks, large language models, generative AI applications, AI technologies

C, Tensorflow, Pytorch, Python, Javascript, data structures, mathematical concepts like probability, object-oriented programming, advanced image processing concepts, numerical methods, linear algebra, Caffe, computer vision algorithms, computer vision libraries, custom algorithms using computer vision ML and foundational models, ML architectures

AWS services, metaheuristics , simulated annealing , Clustering, Aws Services, Artificial Neural Networks, genetic algorithms, branch and cut, branch and bound, Airflow, Kubeflow, Gurobi, workflow orchestration tools, mathematical optimization techniques, combinatorial optimization techniques, AWS Sagemaker, SageMaker Pipelines, machine learning techniques, StepFunctions, MLOps principles, decision tree learning, cloud ML solutions on AWS