Top Tweets for #WholeSemesterInML

over 7 years ago

Days 13-14: It took me some time, but I did it. I prepared the dataset for my WDI workshop. I also prepared myself to implement YOLO model with Keras. https://t.co/NKoE7zAlrY #WholeSemesterInML

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over 7 years ago

Day 10&11: During those two days I studied kaggle data set and learned how to configure pandas with sql databases. Also I started learning about NLP using nltk #WholeSemesterInML

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over 7 years ago

Day 12: Tonight I finished my job at 3 a.m. and after that, I started my challenge for the day before the night. Read some articles about Siamese NNs and a bit about statistics. https://t.co/vxj67Lg6KH #WholeSemesterInML

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over 7 years ago

Day 11: Yesterday I did some research for the challenge but forgot to tweet before shutting down my laptop. Some RL stuff and a preview of YOLO model. https://t.co/ZiN9Yn3SXx #WholeSemesterInML

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over 7 years ago

Day 10: I started the chapter about statistical inference and read some articles about Q Learning and Deep Q Networks in preparation for implementation second of these on my own. https://t.co/CKxQsm04nY #WholeSemesterInML

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over 7 years ago

Day 9: I wrote a test on basic ML learned this week on edx. Then I watched some Numpy videos and revised myself the commands. #WholeSemesterInML

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over 7 years ago

Day 9: Yesterday I got my back a bit broken, so this whole day I've been performing acrobatics with my laptop, cables, food and bed. Finally, I won the battle and in the result, I finished ML course from Coursera https://t.co/tRyqPx0MZl #WholeSemesterInML

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over 7 years ago

I finally got time in work to dive into implementation details of BERT 😃, also watched some of the probabilistic graphical models lectures on coursera #WholeSemesterInML

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over 7 years ago

Day 8: I learned regression analysis using scikit-learn. I used a European Soccer Database and predicted the overall results of players by analysing their statistics. https://t.co/SiAPcQgS9j #WholeSemesterInML

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over 7 years ago

Day 8: After a short break I continued my pandas exploration. I also started the new course called Modern Pandas. Also, have some interesting refs, enjoy https://t.co/joxHqZnUlG #WholeSemesterInML

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over 7 years ago

Day 6&7: I was quite busy lately, but still managed to work on a mini-project. I studied weather data from San Diego from last 5 years and learned about clustering in ML on example. #WholeSemesterInML

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over 7 years ago

Day 7: Some basic algorithmic approaches for recommender systems and the end of the probability theory chapter reached https://t.co/VVRAKsy9BJ #WholeSemesterInML

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over 7 years ago

Day 4: Trying to alter NLP with other ML domains in my research I investigate supervising learning for CV by looking into these this decent slides: https://t.co/sVde9vP8Tc. I wasn't aware at all that it is a real thing in other than LM tasks... #WholeSemesterInML

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over 7 years ago

Day 6: I read the paper about asynchronous deep reinforcement learning for my master thesis and continued statistics book. https://t.co/Tu2MxxuYGg #WholeSemesterInML

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over 7 years ago

Day 3: I've used USE a few times before but acually never care to read the papier, so i gave it a try: https://t.co/IWDQHMPGPl "our model demonstrates weaker associations than GloVe for probes targeted at revealing at ageism, racism and sexism" 💙 #WholeSemesterInML

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over 7 years ago

Day 5: I think I've worked about 1.5h today but in 6 or even more chunks. Anyway, I continued my overview of pandas. https://t.co/FEXvykz1E3 #WholeSemesterInML

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over 7 years ago

Day 5: Continued to read the Data Science Handbook. Revised myself the concept of magic commands in Python and command line in IPython. #WholeSemesterInML

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over 7 years ago

Day 2: Played around with official code for BERT and tried to split the large version of this model to fit in 2x11GB GPU - yet unsuccessfully. Also went through these excellent slides about progress in DL (Yann LeCun): https://t.co/aWezeRg8gB #WholeSemesterInML

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