Machine Learning, Pandas, Docker, Spark, Sql, Python, Kubernetes, Generative AI, LLM technologies

Python, Data Science, Machine Learning, Deep Learning, Model evaluation and validation techniques, Time-series analysis, Data Science and ML libraries, Responsible and explainable AI concepts

Jax, Tensorflow, Pytorch, Python, Stable Baselines3, MuJoCo, Ray RLlib, CleanRL, Gymnasium

Pandas, XGBoost, Spark, Databricks, Python, SHAP, scikit-learn, LightGBM, MLflow, model observability, LIME, Delta Lake, explainability frameworks, drift detection

Java, Golang, Machine Learning, Scala, Microservices, Spark, Databricks, Python, AWS, Statistics, LangChain, GenAI, LangGraph, distributed data processing frameworks, MLFlow

Arm, Sql, MLops, Terraform, Microsoft Azure, Azure Machine Learning, Python, Infrastructure as Code, ServiceNow AI ML, Virtual Agent, API-based integrations, Azure OpenAI, Kore.ai XO Platform, Azure AI Services, CI CD pipelines, Predictive Intelligence, Bicep

Pandas, XGBoost, Tensorflow, Nlp, Numpy, Gcp, Pytorch, Python, LangChain, Vision AI, Cloud platforms, Scikit-learn, Gen AI, Document extraction, Conversational AI

AWS, Nltk, Natural Language Processing, Apache Spark, Tensorflow, Pandas, Pytorch, Gcp, Databricks, Azure, Langchain, scikit-learn, HuggingFace, vector databases, mlflow, gensim, OpenAI, fine-tuning LLMs

Django, FastAPI, Microservices, Python, Flask, Distributed Systems, Machine Learning