Machine Learning, Python, Sql, Deep Learning frameworks, Model Registries, Statistical Models, Feature Stores, Gradient Boosting

Drift detection (e.g. Evidently), PostgreSQL, Sql, Numpy, Pandas, Docker, XGBoost, Python, scikit-learn, LightGBM, CatBoost, Hyperparameter optimisation, SHAP, AWS-hosted infrastructure, Automated retraining pipelines, Feature engineering, Model evaluation

Sql, Tensorflow, Hadoop, Tableau, Power Bi, Pytorch, Oracle Cloud, Machine Learning Algorithms, Big Data Technologies, Predictive Analytics, Google Cloud, AWS, Python, Azure, Spark, applied modeling workflows, feature engineering, deep learning frameworks, cloud platforms, data preprocessing, decision-support systems, Statistical Modeling, data visualization tools, R, AI-powered solutions, model evaluation, analytics platforms, Generative AI, prompt engineering

.NET, Sql, Tensorflow, Pytorch, Java, MLops, Pandas, Data Science, Angular, Scipy, Scala, Blockchain, Internet Of Things, Cloudera, Matplotlib, Numpy, Pyspark, AWS, Artificial Intelligence, Php, Python, Microsoft Azure Cloud, GCP Google Cloud Platform, Scikit-learn, Spark-mllib, Security

prophet , Sql, Deep Learning, Tensorflow, Predictive Modeling, Pytorch, k-means, XGBoost, Keras, Svm, Machine Learning, Random Forest, Python, Arima, Statistical Methods, Time-Series Forecasting, Gaussian Mixture Models, Airflow, scikit-learn, LSTM, collaborative filtering, Customer Segmentation, Recommendation Systems, Clustering Techniques, MLflow, Kubeflow, Hybrid Models