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Explore how generative AI revolutionizes data analytics, streamlining tasks, transforming workflows, and ensuring ethical practices. Gain practical insights and real-world applications for data professionals.
Learn to create interactive data apps using KNIME's low-code/no-code approach. Discover how to build, visualize, and deploy analytics solutions with user-friendly interfaces for end-users to gather insights effortlessly.
Explore text mining and NLP techniques using KNIME Analytics Platform. Learn sentiment analysis, topic extraction, and build a real-time tweet analysis app in this no-code tutorial.
Explore advanced ChatGPT prompting techniques, from freeform to structured formats. Learn scientific principles, master fundamentals, and acquire skills in chain-of-thought and skeleton prompts for optimal results with large language models.
Learn to combine AI and BI for maximum business value. Discover how to identify and assess AI use cases, explore common applications in BI, and see a live demo of PDF text extraction using computer vision.
Learn effective data visualization techniques to transform insights into impactful stories. Covers chart theory, Python coding with pandas and plotly, and practical tips for creating compelling, interactive visualizations.
Explore tokenization in NLP, from basics to advanced techniques. Learn about word embeddings, text splitting, BytePair Encoding, and token vectorization for enhanced language model performance.
Comprehensive overview of recommender systems, covering types, models, performance metrics, and design considerations. Equips learners with knowledge to create and evaluate effective recommendation systems.
Explore how JavaScript, TensorFlow.js, and React Native can enhance melanoma detection accuracy, aiding early skin cancer diagnosis and potentially saving lives through innovative technology.
Explore LINQ in C#: SQL-like syntax for data manipulation. Learn basic queries, filters, joins, grouping, and standard operators to enhance your coding efficiency and data handling skills.
Comprehensive guide to building an attrition recommendation system, covering data analysis, predictive modeling, and strategy development to prevent employee churn and improve workforce retention.
Comprehensive introduction to Naive Bayes classification, covering theory and practical applications through R coding examples, from probability basics to real-world predictive models.
Discover five key strategies for data scientists to excel beyond technical skills, focusing on business translation, relationship building, and controlling the data narrative to advance their careers.
Learn best practices for integrating responsible AI principles throughout the product development lifecycle, focusing on fairness assessment and practical implementation strategies.
Enhance data engineering with behavioral science insights. Learn to create tailored variables, understand behavior drivers, and apply causal analytics for more accurate predictions and effective actions.
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