Adjusting, organizing, and transforming data to make it more accessible.
Adjusting, organizing, and transforming data to make it more accessible.
Identifying and correcting errors and inconsistencies in data.
Streamlining machine learning from development to production.
Training, and evaluating a model to optimize its accuracy and performance on specific tasks.
Reinforcement learning
Natural Language Processing
Computer Vision
Time Series
Supervised Learning
Unsupervised Learning
Tabular Data
Hypothesis testing by collecting and interpreting data to reveal patterns for decision making.