PyData 2017 held in Amsterdam includes talks on machine learning, deep learning and NLP. The content involved applications, tools and hands-on sessions.
Stay up-to-date on the latest data science and AI news in the worlds of artificial intelligence, machine learning, deep learning, implementation, and more.
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In this video we will be discussing about the different types of Feature Engineering Encoding TechniquesSupport me on Patreon: https://www.patreon.com/join/2...
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This video will help you to understand how we can make use of K-Means Clustering algorithm for solving unsupervised learning problem. We will mathematically ...
When trained on large datasets, MLP-Mixer attains competitive scores on image classification benchmarks.
Data cleaning is a subject briefly touched in your brick&mortar or on-line classes. However, in your work as a Data Engineer or Data Scientist, you will spend a great deal of your time getting ready…
Difference between machine learning & deep learning (ML Vs DL) along with the comparison between the two in the field of data science.Explained with examples.
Abstract – Big data helps to make strategy for future and understand user behaviors. In 1959, Arther Samuel gave very simple definition of Machine Learning as “a Field of study that gives computer the ability to learn without being explicitly programmed”. Now almost after 58 years from then we still have not progressed much beyond this definition… Read More »Machine Learning in Fintech – Demystified
Facebook AI Releases 'Dynabench', A Dynamic Benchmark Testing Platform For Machine Learning Systems.
This collection of data science cheat sheets is not a cheat sheet dump, but a curated list of reference materials spanning a number of disciplines and tools.
Welcome to our YouTube channel, which is about the true facts on computer science, it gives you short and sweet and fast information about computer science, ...
Learn about machine learning and AI with this comprehensive 11-hour course from @LunarTech_ai. This is not just a crash course. This course covers everything...
Machine learning code can be notoriously difficult to debug with bugs that are expensive to chase. Even for simple, feedforward neural networks, you often have to make several decisions around…
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Mix-and-match approaches for visualizing data and interpreting machine learning models and results.
