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True to its name, ExplainableAI refers to the tools and methods that explainAI systems and how they arrive at a certain output. Artificial Intelligence (AI) models assist across various domains, from regression-based forecasting models to complex object detection algorithms in deep learning.
Sweetviz GitHub | Website Sweetviz is an open-source Python library that generates beautiful, high-density visualizations to kickstart EDA (Exploratory Data Analysis) with just two lines of code. Apache Superset GitHub | Website Apache Superset is a must-try project for any MLengineer, data scientist, or data analyst.
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Knowledge and skills in the organization Evaluate the level of expertise and experience of your ML team and choose a tool that matches their skill set and learning curve. For example, if your team is proficient in Python and R, you may want an MLOps tool that supports open data formats like Parquet, JSON, CSV, etc.,
Machine Learning Engineer with AWS Professional Services. She is passionate about developing, deploying, and explainingAI/ ML solutions across various domains. Prior to this role, she led multiple initiatives as a data scientist and MLengineer with top global firms in the financial and retail space.
AI comprises Natural Language Processing, computer vision, and robotics. ML focuses on algorithms like decision trees, neural networks, and support vector machines for pattern recognition. Skills Proficiency in programming languages (Python, R), statistical analysis, and domain expertise are crucial.
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