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Explore AI's current limitations, future potential, and research directions towards Artificial General Intelligence in this insightful presentation by Eric Steinberger.
Learn to develop an end-to-end iOS app using Apple's machine learning tools, Create ML and CoreML, for on-device AI without data transmission.
Explore AI's role in enhancing workplace productivity, enabling better insights, and improving business processes. Learn about integrating AI into existing tools for more intelligent and contextualized experiences.
Explore Keras, a user-friendly deep learning API, to make AI accessible for solving business problems. Learn about its features, APIs, model building, and integration with TensorFlow.
Explore state-of-the-art deep learning techniques for recommender systems, including collaborative filtering, content-based methods, and complex architectures like autoencoders and RNNs for personalized recommendations.
Explore AI applications in humanoid robots, including current functions and future developments. Learn about the differences between natural and artificial intelligence in human-robot interactions.
Explore machine learning in hand prostheses that adapt to users, enhancing control and functionality. Learn about challenges, solutions, and future developments in this innovative field.
Explore the paradigm shift in AI adoption, its impact across industries, and strategies for successful AI projects. Learn how developers can leverage AI to create innovative solutions and drive positive change.
Explore an interactive DIY tool for non-data scientists to train and deploy classifiers, simplifying topic identification in large document sets with minimal data collection and quick model training and tuning.
Learn to classify millions of messages using trained deep learning models (fasttext) with Spark. Includes explanations of key concepts and a practical demo on model training and message classification.
Explore augmented intelligence, combining human and machine strengths for enhanced decision-making. Learn about its benefits, challenges, and real-world applications in various industries.
Explore the challenges of obtaining quality data for AI applications in security and other fields, focusing on data acquisition methods and assessing data quality for effective research and development.
Explore Ocean Protocol's decentralized marketplace for AI data, enabling secure sharing and monetization while preserving privacy and control for data owners and consumers.
Explore the Team Data Science Process (TDSP) for efficient predictive analytics and AI integration in business processes, focusing on agile methodology and practical implementation strategies.
Explore AI and advanced analytics applications in banking, focusing on Raffeisen Bank International's innovative approaches to data-driven decision-making and customer service enhancement.
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