Excel, Python, Deep Learning, ML Algorithms

Pyspark, Logistic Regression, Machine Learning, Svm, Azure Databricks, Clustering, Random Forest, XGBoost, Python, Data Pipelines, scikit-learn, MLlib, h2o, GLM Regression, R, Data Analysis, Statistical Modeling

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

Data Manipulation, Hadoop, Adf, Sql, Spark, Azure cloud services, Big Data, Python, Machine Learning Algorithms, Azure DevOps, data preprocessing, Agile framework, Feature Stores, CI CD pipelines, ML engineering, feature engineering, MLFlow

Java, Tensorflow, Pytorch, Python, Springboot, Kusto, Google BigQuery, multi-agent orchestration, tree-based models, Statistical Techniques, anomaly detection, agent-to-agent communications, streaming ML, distributed infrastructure, autonomous decision-making workflows

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

Azure, Tensorflow, AWS, Pytorch, Python, Kubernetes, Cloud Infrastructure, Docker, Gcp, distributed training, model serving frameworks, inference at scale, ML frameworks, Hugging Face Transformers, metrics for language models, model optimisation, evaluation methodologies

Sql, Asynchronous programming, Pandas, Numpy, MLops, Docker, Spark, Restful Apis, Kubernetes, Python, Airflow, Infrastructure as Code, Automated training and deployment pipelines, scikit-learn, Model versioning, Prefect, CI CD for ML systems, Dagster, Experiment tracking, statsmodels, Data ingestion pipelines

Data structures, Algorithms, Pytorch, Python, SW architecture, AI ML solutions, Quantization techniques, Machine learning compiler techniques, Design philosophies, Machine learning runtimes, ONNX, Machine learning compilers, Deep learning frameworks, SW design patterns