Top ML Reddit Discussions, NLP Roadmap & Much More!

Top 5 Machine Learning GitHub Repositories & Reddit Discussions

Why do we include Reddit discussions in this series? I have personally found Reddit an incredibly rewarding platform for a number of reasons — rich content, top machine learning/deep learning experts taking the time to propound their thoughts, a stunning variety of topics, open-source resources, etc. I always try to include at least one reinforcement learning repository in these lists — primarily because I feel everyone in this field should be aware of the latest advancements in this space. Will autoML be ruling the roost? How will the hardware have advanced? Will there finally be official rules and policies around ethics? Will machine learning have integrated itself into the very fabric of society? Will reinforcement learning finally have found a place in the industry? These are just some of the many thoughts propounded in this discussion. This is where Reddit becomes so useful — you can pitch your idea in this discussion and you’ll receive feedback from the community on how you can approach the challenge.

You can check out the original article here.

Level: Advanced


Tryst with Deep Learning in International Data Science Game

  • Since a quantum leap was required to capture the higher level of abstraction present in the data like complex edge patterns, shapes, different color blobs, etc., it was needed to choose a model which can bring in the complexity in feature generation.
  • Our strategy was to label the images, using the already trained network, with the hope that the volume advantage of having an increased dataset for training is more than the losses due to noise in the added dataset.
  • The overall experience shows the power of a Deep network acting as an oracle in deciding about the labels for unlabeled data and in turn using that imparted knowledge to make itself better learned.
  • As to the construct of the experiment, every time the network has been fed by a slightly different but bigger dataset, in different instances of training, it is possible to store different models which have the potential to predict with almost similar accuracy. To some extent, this time can be minimized by generating images for augmentation on the fly in Keras, which is primarily due to less time required for seeking files on the disk.

You can check out the original article here.

Level: Beginner


A Complete Roadmap to prepare for Natural Language Processing



I hope you found this blog post insightful. Please do share it with your friends & family. You can reach out to me on LinkedIn. I am quite active here & I will be happy to have a conversation with you. Please feel free to drop your feedback in the comments that helps me to improve the quality of my work. I will keep on sharing more content as I grow & mature as a Data Scientist. Until next time, Keep Hustling & Keep Up with Data Science. Happy Learning 🙂

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