Difference between revisions of "User:Skohli"
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*Met Dr. Povinelli 2 times to discuss current progress | *Met Dr. Povinelli 2 times to discuss current progress | ||
*Collected data | *Collected data | ||
+ | '''Week 4 (June 19 - June 23)''' | ||
+ | *Go through Machine Learning tutorials online | ||
+ | *Try to learn tensorflow | ||
+ | *Try to learn Quantile regression | ||
+ | *Understand Pinball Loss Function | ||
+ | '''Week 5(June 26 - June 30)''' | ||
+ | *Prepare slides for presentation | ||
+ | *Present presentation | ||
+ | *Work with Keras | ||
+ | *Make prelimary models | ||
+ | *Wish for faster computers | ||
+ | *Implement the pinball loss function with different methods: | ||
+ | **Convolutional neural networks | ||
+ | **ResNets | ||
+ | **Feed Forward | ||
+ | ***Keras api for models | ||
+ | *** WIthout Keras api for models | ||
+ | *Implement the Winkler Score | ||
+ | *Read Attention is all you need | ||
+ | '''Week 6 (July 3 - July 6)''' | ||
+ | *https://arxiv.org/pdf/1706.02515.pdf | ||
+ | *Tried different deep learning techniques | ||
+ | **CNN | ||
+ | **ResNet | ||
+ | **RNNS | ||
+ | **Feed forward | ||
+ | ***Hyperamaters | ||
+ | *Presented at GasDay | ||
+ | *Attended how to make a good poster presentation | ||
+ | '''Week 7 (July 8 - July 15)''' | ||
+ | *Adapted the technique from DeepAR | ||
+ | *Tried different methods surrounding it | ||
+ | *Choose which method I will stick with | ||
+ | '''Week 8(July 17- July 21)''' | ||
+ | *Spent week trying to see why val and test scores are extremely different | ||
+ | *Ran models with different data sets to see why that is happening | ||
+ | '''Week 9(July 24 - July 28)''' | ||
+ | *Finishing up poster | ||
+ | *Finishing up presentation | ||
+ | *Starting to write paper | ||
+ | *Cleaning code | ||
+ | *Present at GasDay | ||
+ | *Make changes to model | ||
+ | *Run final models | ||
+ | '''Week 10(July 31 - August4)''' | ||
+ | *Prepared for poster session | ||
+ | *Prepared final presentation | ||
+ | *Finished paper |
Latest revision as of 15:23, 2 August 2017
Personal Information
- Incoming junior | Computer science major at Marquette
- Working with Dr. Povinelli in the GasDay Lab
Weekly Log
Week 1 (May 30 - June 2)
- Discussed preliminary project ideas with other researchers and mentor.
- Attended library tour.
- Attended the talk on how to conduct research.
- Read paper on the GEFcomp2014- Hongetal2016
- Read Bengio Learning Deep Architectures for AI
- Found more material to read.
- Attended weekly book club meeting as suggested by mentor
- Read chapter 1-3 in the book titled Deep Learning Book
- Read Probabilistic Forecasting by Gneting and Katzfuss
- Additive models and robust aggregation for GEFcomp2014 probabilistic electric load and electricity price forecasting by Gaillard, Goude, Nedellec.
- Read DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks
- Met Dr. Povinelli 4 times: to discuss possible project topics, to get oriented with the lab, to decide on a project topic, and to establish weekly milestones
Week 2 (June 5 - June 9)
- Read chapter 4 of deep neural network book
- Attended GasDay camp
- Learned what GasDay does
- Benefits of working at GasDay
- Further research opportunities at GasDay
- How to work in a team
- Attended the Ethical research training
- Learned key concepts such as not fabricating, falsifying, and plagiarizing
- Read
- 10.1109/PMAPS.2016.7764155
- https://doi.org/10.1016/j.energy.2016.07.090
- http://www.sciencedirect.com/science/article/pii/S1568494617302946
- Met Dr. Povinelli 3 times to discuss current progress
- Attended weekly book club meeting as suggested by mentor
Week 3 (June 12 - June 16)
- Tasks undertaken to improve skills
- Completed 6 weeks of the coursera tutorial on Machine Learning
- Completed 6 weeks of the Stanford class on Convolution Neural Networks for Visual Recognition
- Learned basics of Python
- Completed portion of online RCR training
- Attended weekly book club meeting as suggested by mentor
- Met Dr. Povinelli 2 times to discuss current progress
- Collected data
Week 4 (June 19 - June 23)
- Go through Machine Learning tutorials online
- Try to learn tensorflow
- Try to learn Quantile regression
- Understand Pinball Loss Function
Week 5(June 26 - June 30)
- Prepare slides for presentation
- Present presentation
- Work with Keras
- Make prelimary models
- Wish for faster computers
- Implement the pinball loss function with different methods:
- Convolutional neural networks
- ResNets
- Feed Forward
- Keras api for models
- WIthout Keras api for models
- Implement the Winkler Score
- Read Attention is all you need
Week 6 (July 3 - July 6)
- https://arxiv.org/pdf/1706.02515.pdf
- Tried different deep learning techniques
- CNN
- ResNet
- RNNS
- Feed forward
- Hyperamaters
- Presented at GasDay
- Attended how to make a good poster presentation
Week 7 (July 8 - July 15)
- Adapted the technique from DeepAR
- Tried different methods surrounding it
- Choose which method I will stick with
Week 8(July 17- July 21)
- Spent week trying to see why val and test scores are extremely different
- Ran models with different data sets to see why that is happening
Week 9(July 24 - July 28)
- Finishing up poster
- Finishing up presentation
- Starting to write paper
- Cleaning code
- Present at GasDay
- Make changes to model
- Run final models
Week 10(July 31 - August4)
- Prepared for poster session
- Prepared final presentation
- Finished paper