Machine Learning, Pyspark, Kafka, Sql, Gcp, Spark, Azure, Devops Tools, Python, Computer Vision, Deep Vision algorithms, infrastructure automation, MLOps practices, model monitoring

Pyspark, Tensorflow, System Design, Python, Computer Vision, Recommendation engines, Generative AI, Vector DBs, Torch, Graph Knowledge Bases, Image Understanding models, Large-scale Search systems

MLops, Pyspark, XGBoost, Python, Sql, Random Forest, Deep Learning, LightGBM

Machine Learning, Tensorflow, Agile Development, Git, Pandas, Linux, Image Processing, Keras, Python, DCS Systems, API Services, Scikit-learn, Statistics, Dynamic Optimization

Predictive Modeling, Machine Learning, Hadoop, Sql, Tensorflow, Pytorch, XGBoost, Spark, Python, Recommendation Systems, R, Data Analysis

Tensorflow, Pytorch, MLops, Docker, Databricks, Keras, Azure, Kubernetes, Python, Delta Lake, MLflow

Cassandra, Pyspark, Svm, Tableau, Tensorflow, Numpy, Python, Hadoop, HBase, Sql, Artificial Neural Networks, Naive Bayes, Hive, Pandas, XGBoost, Spark, Databricks, Keras, MongoDB, Aws S3, machine learning techniques, k-NN, Decision Forests, Map Reduce, NoSQL databases, Scikit-learn, SageMaker, Athena

bayesian inference , Git, Statistical Inference, Docker, Maven, Apache Spark, Hypothesis Testing, Machine Learning Algorithms, Kubernetes, Python

Version Control, Databricks, Python, R, Qualitative Analysis, Applied Statistics

regression models , snowflake , Unix, Github, Pyspark, Nlp, Pytorch, Python, AWS, Sql, Deep Learning, Git, Pandas, Linux, Decision Trees, Spark, Databricks, Azure, Matrix Factorization, VS Code, Content-Based Filtering, Time-Series Forecasting, Neural Collaborative Filtering, LLMs, Segmentation techniques, Scikit-learn, Unsupervised Clustering, collaborative filtering