Machine learning techniques

Data Science, Machine Learning, Data Analysis, Data Processing

Docker, FastAPI, Kubernetes, Python, Sql, AWS, Airflow, Dataiku, CPLEX, OR-Tools, Pulp

prophet , Machine Learning, Scipy, Random Forest, Deep Learning, Tensorflow, Numpy, Pandas, MLops, Pytorch, XGBoost, Arima, Databricks, Python, LSTM, scikit-learn, SARIMA, GRU, Time Series Forecasting, TimeGPT, statsmodels

causal inference , Machine Learning, Hadoop, Sql, Hive, MLops, Spark, Python, Generative AI, Optimization, Statistical Measurement, Operations Research, AI Engineering, Simulation

data engineering , Large Language Models (LLMs), Statistical Analysis, Machine Learning, Data Governance, Sql, MLops, Python, Prescriptive modeling, Semantic Layers, Feature engineering, Agent orchestration frameworks, Embeddings, LLM APIs, Real-time anomaly detection models, ML pipelines, RAG, Large-scale data processing systems, AI agents

Sql, Pandas, Spark, Predictive Modelling, Python, Statistical Modelling, Data Strategy, Cloud platforms, Matching algorithms, Lift analyses, MLOps practices, Jupyter, AI agents

Machine Learning, Model Monitoring, AI Governance, Feature Engineering, Prompt Engineering, Statistical Modeling, Generative AI, Performance Evaluation

Apache Spark, Sql, Tensorflow, Pytorch, Opencv, Databricks, Azure, Python, AWS, Scikit-learn, TorchVision, R