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Recognize Class Imbalance with Baselines and Better Metrics
Editor’s Note: Samuel is speaking at ODSC West 2019, see his talk “Help! My Classes are Imbalanced” there. In my first machine learning course as an undergrad, I built a recommender system. Using a dataset from a social music website, I created a model to predict whether a given... Read more
Not Always a Black Box: Machine Learning Approaches For Model Explainability
Editor’s Note: Violeta is speaking at ODSC Europe 2019, see her talk “Not Always a Black Box: Explainability Applications for a Real Estate Problem“ What is model explainability? Imagine that you have built a very precise machine learning model by using clever tricks and non-standard features. You are beyond... Read more
Causal Inference: An Indispensable Set of Techniques for Your Data Science Toolkit
Editor’s Note: Want to learn more about key causal inference techniques, including those at the intersection of machine learning and causal inference? Attend ODSC West 2019 and join Vinod’s talk, “An Introduction to Causal Inference in Data Science.” Data scientists often get asked questions of the form “Does X... Read more
Bears Need to Learn as well – Practical Reinforcement Learning with TensorFlow 2.0 & TF-Agents
Editor’s Note: Oliver is speaking at ODSC West 2019, see his talk “Reinforcement Learning with TF Agents & TensorFlow 2.0: Hands On” there. Have a look at our friend Orso the bear.  Orso lives in his cave and knows his area and where he can typically find some honey.... Read more
Automating Data Wrangling – The Next Machine Learning Frontier
Editor’s note: Be sure to check out Alex’s talk at ODSC West 2019 this November, “The Last Frontier of Machine Learning – Data Wrangling.” Up to 95% of a data scientist’s time is spent data wrangling. Conversely, about 99% of data-scientists hate data wrangling. That’s problematic. Data wrangling tends... Read more
Ben Vigoda on the New Era of NLP
Many apps and programs claim to be able to understand you and are at least capable of engaging in superficial interactions. Spend long enough talking to one of these programs, however, and you’ll no doubt see the hallmarks of imperfectly reproduced natural language. That technology has not yet caught... Read more
Watch: Introduction to Machine Learning with Scikit-Learn
Machine learning has become an indispensable tool across many areas of research and commercial applications. From text-to-speech for your phone to detecting the Higgs-Boson particle, machine learning excels at extracting knowledge from large amounts of data. This talk gives a general introduction to machine learning and introduces practical tools... Read more
Watch: Deploying Investments in AI and Machine Learning
Over the next 18 months, companies will be completing the R&D phase of their AI/ML investments and will be deploying their models and algorithms to production. The proper execution of deploying your AI/ML models will separate the organizations who see an ROI on AI from those who don’t. This... Read more
Watch: High-Performance Data Science with Docker and Digital Ocean
This talk discusses Docker as a tool for data scientists, in particular in conjunction with the popular interactive programming platform, Jupyter, and the cloud computing platform, Amazon Web Services (AWS). Using Docker, Jupyter, and AWS, a data scientist can take control of their environment configuration, prototype scalable data architectures,... Read more
Watch: Applications of Deep Learning in Aerospace
Recent advances in machine learning techniques such as deep learning (DL) have rejuvenated data-driven analysis in aerospace and integrated building systems. DL algorithms have been successful due to the presence of large volumes of data and its ability to learn the features during the learning process. The performance improvement... Read more