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India banned Telegram after the NEET paper leak led to a retest for 2.28 million students. Class Central studied the scam, the money trail, and other platforms the leaks could move to.
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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.
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.
Comprehensive overview of recommender systems, covering types, models, performance metrics, and design considerations. Equips learners with knowledge to create and evaluate effective recommendation systems.
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.
Discover how to build scalable multi-agent AI systems using LangChain, exploring design patterns, orchestration techniques, and production-ready architectures beyond single agents.
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.
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.
Explore strategies to accelerate and automate AI/ML workflows using Kubernetes, leveraging open-source tools like Jupyter Notebooks and TensorFlow for efficient development and deployment.
Discover how to build Agentic AI for semantic search using Pinecone vector databases and AWS services through hands-on RAG chat application development.
Discover how to build autonomous AI systems with persistent reasoning using LangGraph, covering planning, memory, sub-agents, and real-world applications for complex workflows.
Discover how to build intelligent multi-agent AI systems using FloTorch's code and no-code approaches for scalable, production-ready workflows with seamless LLM integration.
Discover how to design domain-specific AI agents for high-stakes environments like healthcare, law, and finance with explainability, compliance, and precision at their core.
Discover how to build and optimize RAG retrievers using LanceDB for high-performing Retrieval-Augmented Generation systems with hands-on strategies and practical implementation techniques.
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