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Explore graph analytics fundamentals, use cases, and applications in fraud detection. Learn how graph technology enhances ML approaches and its growing importance in complex data analysis.
Learn to streamline machine learning model development with Azure AutoML. Explore algorithm selection, hyperparameter tuning, and evaluation metrics for efficient model creation and deployment.
Learn to set up and use MySQL for data science, covering RDBMS basics, deployment, interfacing, and practical dataset examples. Gain essential SQL skills for working with structured data in real-world scenarios.
Explore the revolutionary ResNet architecture, its impact on deep learning, and hands-on image classification. Learn about CNN limitations and how ResNet's skip connections transformed the field.
Learn effective data storytelling techniques using the 3Vs: Vocabulary, Voice, and Vision. Improve your ability to create compelling narratives for data management programs and gain support from stakeholders.
Learn essential SQL data wrangling techniques for querying, joining, appending, filtering, and creating new fields in datasets. Gain practical skills to efficiently prepare and transform data for analysis.
Learn effective data storytelling techniques to enhance data analysis impact. Discover how to use visualizations, narratives, and creative approaches to make insights more relatable and actionable for businesses.
Learn effective data storytelling techniques to transform raw information into compelling narratives. Discover how to analyze, visualize, and communicate insights for evidence-informed decision-making in organizations.
Explore methods for interpreting machine learning models, including feature importance and local explanations, to increase trust in AI products and bridge gaps in problem understanding.
Learn to deploy ML models as web services using Flask, manage environments with Pipenv, package with Docker, and deploy to AWS Beanstalk. Gain practical skills for putting models into production.
Explore quantum generative machine learning, combining quantum computing and data generation. Learn about quantum bits, measurement, entanglement, and practical applications using the Quantum Circuit Born Machine.
Discover a tool-agnostic framework for effective data handling, emphasizing process over tools. Learn to adapt to new technologies and understand the importance of data literacy in today's changing landscape.
Explore codeless deep learning with KNIME Analytics Platform. Learn neural network basics, convolutional networks for computer vision, and build a classification model using KNIME's Keras integration.
Learn time series analysis using KNIME: preprocessing, alignment, imputation, forecasting, and evaluation. Build a demand prediction application with (S)ARIMA and machine learning models through hands-on, codeless examples.
Learn a systematic process to leverage machine learning for improved decision-making, focusing on actionable metrics, key levers, and embracing uncertainty to drive better business outcomes.
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