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Data Preparation for Predictive Analytics
This one-day session will expose analytics practitioners, data scientists, and those looking to get started in predictive analytics to the critical importance of selecting, transforming, and properly preparing data ahead of model building.
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Hands-On: Data Manipulation and Cleaning in Python
Data manipulation and cleaning in machine learning is estimated to take more than 50% of the time allotted for any given machine learning project. This course will cover topics important in handling structured and unstructured data, scraping data in Python, including using key packages such as Pandas, NumPy, and Matplotlib.
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Introduction to Data Wrangling
This course addresses how to translate the problem statement, identifying data sources, exploring the data for relationships and recognize patterns, identifying the starting inputs for the model, preparing data, and validating it for the model fitting process.
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TDWI Data Quality Management
This course is designed to help your organization better understand and successfully tackle your data quality challenges.
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Data Science Bootcamp Day 2:
Supervised and Unsupervised Modeling
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TDWI Data Quality Management: Techniques for Data Profiling, Assessment, and Improvement
The only proven path to sustainable data quality is through a comprehensive quality management program that includes data profiling, data quality assessment, root cause analysis, data cleansing, and process improvement.
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Data Science Bootcamp Day 2:
Supervised and Unsupervised Modeling
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Supervised Machine Learning: Preparing Data and Deploying Analytic Models for Classification and Prediction
Regression, decision trees, neural networks—along with many other supervised learning techniques—provide powerful predictive insights. These data-driven insights inform the forces shaping your organization’s outcomes.
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TDWI Data Quality Management: Techniques for Data Profiling, Assessment, and Improvement
The only proven path to sustainable data quality is through a comprehensive quality management program that includes data profiling, data quality assessment, root cause analysis, data cleansing, and process improvement.
more