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Top Resources for Deep learningPosted by Admin
There are many resources for deep learning on the web. We at Sublime AI have tried a bunch of them and concluded that these are the best one for coders.- Practical Deep Learning For Coders
- Linear Algebra for Deep Learning
- Deep Learning for NLP (without Magic)
- Keras and Lasagne Deep Learning Tutorials
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Non Consumer Application of Deep LearningPosted by Admin
Deep Learning is well known for Consumer Applications. But we at Sublime AI are interested in non consumer / enterprise applications. Here are the few innovative ones we found- Discovery of New Materials
- Warehouse Optimization
- Brain Tumor Detection
- Reducing your Electric Bill
- Stocking Shelves
- Predicting Clinical Events
- Bioinformatics
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Read the preprint version of the paper at https://psyarxiv.com/hv28a/.
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Deep Neural Networks Detect Sexual Orientation From FacesPosted by Admin
A recent paper (due to be published in the Journal of Personal and Social Psychology) by Stanford researchers Yilun Wang and Michal Kosinski on detecting people’s sexuality using a few facial images has created turmoil in two different communities; contrastingly for the delight of one and dismay of the other.Read the preprint version of the paper at https://psyarxiv.com/hv28a/.
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Andrew patiently explains the requisite math and programming concepts in a carefully planned order and a well regulated pace suitable for learners who could be rusty in math/coding. Programming assignments are done via Jupyter notebooks — powerful browser based applications. f you have not done any machine learning before this, don’t take this course first. The best starting point is Andrew’s original ML course on coursera.
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Thoughts after taking the Deeplearning.ai coursesPosted by Admin
Andrew Ng’s new adventure is a bottom-up approach to teaching neural networks — powerful non-linearity learning algorithms, at a beginner-mid level.Andrew patiently explains the requisite math and programming concepts in a carefully planned order and a well regulated pace suitable for learners who could be rusty in math/coding. Programming assignments are done via Jupyter notebooks — powerful browser based applications. f you have not done any machine learning before this, don’t take this course first. The best starting point is Andrew’s original ML course on coursera.
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