30-days-of-Udacity

What is the #30DaysofUdacity challenge?

The premise of this challenge is to build a habit of practicing new skills by making a public commitment of practicing the topic of your program every day for 30 days.

Why?

Because habits that emphasize consistent practice have been proven to help overall retention of new learning material.

Daily logs

Day 1: 2019. 09. 08.

1. Pledged to participate in the challenge
2. 30-days-of-Udacity Github repository created. It can be found here: https://github.com/anitagold/30-days-of-Udacity
3. Deep Learning Nanodegree - Section 1: Introduction to Deep Learning - Lesson 1-2 finished
4. In Career Portal career profile updated
5. Deep Learning Nanodegree - Section 1: Introduction to Deep Learning - Lesson 3-4 finished

Day 2: 2019. 09. 09.

1. Deep Learning Nanodegree - Section 1: Introduction to Deep Learning - Lesson 5 finished
2. Deep Learning Nanodegree - Section 1: Introduction to Deep Learning - Lesson 6 started

Day 3: 2019. 09. 10.

1. Deep Learning Nanodegree - Section 1: Introduction to Deep Learning - Lesson 6 finished. @Archit, @MD BAPPI P., congrats and keep up the good work!

Day 4: 2019. 09. 11.

1. Deep Learning Nanodegree - Section 1: Introduction to Deep Learning - Lesson 7 - Concepts 1-7 finished.

Day 5: 2019. 09. 12.

1. Deep Learning Nanodegree - Section 1: Introduction to Deep Learning - Lesson 7 finished.

Day 6: 2019. 09. 13.

1. Deep Learning Nanodegree - Section 1: Introduction to Deep Learning - Lesson 8 - Concepts 1-8 finished.

Day 7: 2019. 09. 14.

1. Since I want strong base I revised Deep Learning Nanodegree - Section 1: Introduction to Deep Learning - Lesson 8 - Concepts 1-8., tried every code sample and have read all the referenced documentation
2. Deep Learning Nanodegree - Section 1: Introduction to Deep Learning - Lesson 8 finished.
3. I've seen a 3Blue1Brown video about Visualizing high-dimensional spheres: https://www.youtube.com/watch?v=zwAD6dRSVyI

Day 8: 2019. 09. 15.

1. Section 2: Neural Networks - Lesson 1: Introduction to Neural Networks - Concepts 1-14 finished.

Day 9: 2019. 09. 16.

1. Section 2: Neural Networks - Lesson 1: Introduction to Neural Networks - Concepts 15-26 finished. @MarwaF , @Archit and @OlgaT keep up the good work!

Day 10: 2019. 09. 17.

1. Section 2: Neural Networks - Lesson 1: Introduction to Neural Networks finished.

Day 11: 2019. 09. 18.

1. Started to work in Project 1. - Predicting Bike-sharing patterns
2. Section 2: Neural Networks - Lesson 2: Implementing Gradient Descent - Concepts 1-4 finished.
3. Practised 20 finished courses in Datacamp (partly ML and DL)
4. Booked an appointment with my mentor

Day 12: 2019. 09. 19.

1. Worked in Project 1. - Predicting Bike-sharing patterns
2. Section 2: Neural Networks - Lesson 2: Implementing Gradient Descent finished.

Day 13: 2019. 09. 20.

1. Section 2: Neural Networks - Lesson 3: Training Neural Networks finished.

Day 14: 2019. 09. 21.

Deep Learning ND:

1. Section 2: Neural Networks - Lesson 4: GPU Workspaces Demo finished.
2. Worked in the first project - Predicting Bike-sharing patterns

Day 15: 2019. 09. 22.

Deep Learning ND:

1. Worked in the first project - Predicting Bike-sharing patterns

Day 16: 2019. 09. 23.

Deep Learning ND:

1. Worked in the first project - Predicting Bike-sharing patterns

Day 17: 2019. 09. 24.

Deep Learning ND:

1. Finished and submitted the first project - Predicting Bike-sharing patterns

Day 18: 2019. 09. 25.

Deep Learning ND:

1. I received the review of the first project. It was accepted.
2. Section 2: Neural Networks - Lesson 6: Sentiment Analysis - Concepts 1-12 finished.

Computer Vision ND:

1. I've set a study plan and I have written an introductory letter to my mentor.
2. Section 1: Introduction to Computer Vision - Lesson 1: Welcome to Computer Vision finished.
3. Section 1: Introduction to Computer Vision - Lesson 2: Welcome to Udacity finished.

Day 19: 2019. 09. 26.

Deep Learning ND:

1. Section 2: Neural Networks - Lesson 6: Sentiment Analysis - Concepts 13-21 finished.

Computer Vision ND:

1. Section 1: Introduction to Computer Vision - Lesson 3: Get Help With Your Account finished.
2. Section 1: Introduction to Computer Vision - Lesson 4: Image Representation & Classification Concepts 1-11 finished. Encouraging @HelenaB , @Imroze , @ZsoltB !

Day 20: 2019. 09. 27.

Deep Learning ND:

1. Section 2: Neural Networks - Lesson 6: Sentiment Analysis finished.
2. Section 2: Neural Networks - Lesson 7: Deep Learning with PyTorch Concepts 1-3 finished.

Computer Vision ND:

1. Section 1: Introduction to Computer Vision - Lesson 4: Image Representation & Classification Concepts 11-15 finished.

Day 21: 2019. 09. 28.

Deep Learning ND:

1. Started to work on project 2.: Dog-Breed Classifier

Day 22: 2019. 09. 29.

Deep Learning ND:

1. Worked on project 2.: Dog-Breed Classifier

Day 23: 09/30/2019.

Deep Learning ND:

1. Section 2: Neural Networks - Lesson 7: Deep Learning with PyTorch Concepts 3-10 finished.

Computer Vision ND:

1. Section 1: Introduction to Computer Vision - Lesson 4: Image Representation & Classification Concepts 15-21 finished.

Day 24: 10/01/2019.

Deep Learning ND:

1. Section 2: Neural Networks - Lesson 7: Deep Learning with PyTorch Concepts 11-20 finished.
2. I watched a podcast clip with Lex Fridman and Jeremy Howard: https://www.youtube.com/watch?v=Bi7f1JSSlh8&list=PLrAXtmErZgOeciFP3CBCIEElOJeitOr41 This is just a short clip, I plan to watch the full episode, because it was very interesting!
3. This podcast was about active learning (in machine learning), so I searched what it is, and I've read the concept here: https://en.wikipedia.org/wiki/Active_learning_(machine_learning)

Computer Vision ND:

1. Section 1: Introduction to Computer Vision - Lesson 4: Image Representation & Classification finished.
2. I've learned more about HSL and HSV color model from Wikipedia: https://en.wikipedia.org/wiki/HSL_and_HSV

Encouragement: Good job, @labibaR and @Mohamed ChoukriB ! Keep up the good work! Great to see you here, @LauraT , @HelenaB , @Juan CarlosK , @OlgaT , @Imroze , @ZsoltB , @FridaR and @Jacqueline SusanM !

Day 25: 10/02/2019.

Deep Learning ND:

1. Section 2: Neural Networks - Lesson 7: Deep Learning with PyTorch finished.
2. I watched the first 40 minutes from this video with Lex Fridman and Jeremy Howard: https://www.youtube.com/watch?v=J6XcP4JOHmk
3. Section 3: Convolutional Neural Networks - Lesson 1: Convolutional Neural Networks - Concepts 1-2 finished

Computer Vision ND:

1. Section 1: Introduction to Computer Vision - Lesson 5: Convolutional Filters and Edge Detection - Concepts 1-14 finished.
2. I've learned more about Fourier Transformations from Wikipedia: https://en.wikipedia.org/wiki/Fourier_transform
3. Revised the suggested Fourier Transformation in OpenCV: https://docs.opencv.org/3.0-beta/doc/py_tutorials/py_imgproc/py_transforms/py_fourier_transform/py_fourier_transform.html

Day 26: 10/03/2019.

Deep Learning ND:

1. Section 3: Convolutional Neural Networks - Lesson 1: Convolutional Neural Networks - Concepts 3-18 finished

Computer Vision ND:

1. Section 1: Introduction to Computer Vision - Lesson 5: Convolutional Filters and Edge Detection finished.

Day 27: 10/04/2019.

Deep Learning ND:

1. Section 3: Convolutional Neural Networks - Lesson 1: Convolutional Neural Networks - Concepts 18-27 finished

Computer Vision ND:

1. Section 1: Introduction to Computer Vision - Lesson 6: Types of Features & Image Segmentation Concepts 1-5 finished.

Day 28: 10/05/2019.

Deep Learning ND:

1. Section 3: Convolutional Neural Networks - Lesson 1: Convolutional Neural Networks - Concepts 27-34 finished

Computer Vision ND:

1. Section 1: Introduction to Computer Vision - Lesson 6: Types of Features & Image Segmentation finished.

Day 29: 10/06/2019.

Deep Learning ND:

1. Section 3: Convolutional Neural Networks - Lesson 1: Convolutional Neural Networks - Concepts 33-39 finished

Computer Vision ND:

1. Started to work on Project 1: Facial Keypoint Detection
2. Section 1: Introduction to Computer Vision - Lesson 7: Feature Vectors finished.
3. Section 1: Introduction to Computer Vision - Lesson 8: CNN Layers and Features Visualization Concepts 1-3 finished.

Day off: 10/07/2019.

Day 30: 10/08/2019.

Deep Learning ND:

1. Section 3: Convolutional Neural Networks - Lesson 1: Convolutional Neural Networks finished.

Computer Vision ND:

1. Continued to work on Project 1: Facial Keypoint Detection
2. Section 1: Introduction to Computer Vision - Lesson 8: CNN Layers and Features Visualization Concepts 3-16 finished.

Day 31: 10/09/2019.

Computer Vision ND:

1. Section 1: Introduction to Computer Vision - Lesson 8: CNN Layers and Features Visualization finished.
2. Worked on the project 1

Day 32: 10/10/2019.

Deep Learning ND:

1. Section 3: Convolutional Neural Networks - Lesson 2: Cloud Computing - Concepts 1-4 finished

Computer Vision ND:

1. Worked on the Project 1: Facial Keypoint Detection Congrats, @Imroze for submitted project 2! Great work, @HelenaB , @ZsoltB and @TemitopeO !

Day 33: 10/11/2019.

Computer Vision ND:

1. Worked on the Project 1: Facial Keypoint Detection

Day 34: 10/12/2019.

Computer Vision ND:

1. Worked on the Project 1: Facial Keypoint Detection
2. Today encouragement goes to @Madison Annika LottieE @UrviS @ApoorvaP @Jess @ShahanaS @Jacqueline SusanM @HelenaB @EileenH @AnjuM @Yemissi K @TemitopeO @labibaR @SusanW @FridaR @SusanneB @AleksandraD @LauraT and all the wonderful women from the women_who_code channel!

Day 35: 10/13/2019.

Computer Vision ND:

1. Worked on the Project 1: Facial Keypoint Detection

Day 36: 10/14/2019.

Deep Learning ND:

1. Section 3: Convolutional Neural Networks - Lesson 2: Cloud Computing finished
2. Section 3: Convolutional Neural Networks - Lesson 3: Transfer learning Concepts 1-3 finished

Computer Vision ND:

1. Worked on the Project 1: Facial Keypoint Detection

Day 37: 10/15/2019.

Deep Learning ND:

1. Section 3: Convolutional Neural Networks - Lesson 3: Transfer learning finished
2. Read Sebastian Thrun's article about skin cancer classification: https://www.nature.com/articles/nature21056.epdf

Computer Vision ND:

1. Worked on the Project 1: Facial Keypoint Detection

Day 38: 10/16/2019.

Deep Learning ND:

1. Section 3: Convolutional Neural Networks - Lesson 4: Weight inilizatoin finished
2. I watched an interesting interview with Christian Szegedy about adversarial examples and the future of deep learning: https://www.youtube.com/watch?v=p_UXra-_ORQ
3. I've read more about adversarial examples: https://medium.com/@ml.at.berkeley/tricking-neural-networks-create-your-own-adversarial-examples-a61eb7620fd8
4. I have finished this ML DataCamp course: https://www.datacamp.com/courses/machine-learning-with-tree-based-models-in-python
5. This was the last course, so I have completed the Data Scientist with Python track on DataCamp.

Computer Vision ND:

1. Worked on the Project 1: Facial Keypoint Detection

Day 39: 10/17/2019.

Deep Learning ND:

1. Section 3: Convolutional Neural Networks - Lesson 5: Autoencoders Concepts 1-9 finished

Day 40: 10/18/2019.

Deep Learning ND:

1. Section 3: Convolutional Neural Networks - Lesson 5: Autoencoders finished

Day 41: 10/19/2019.

Deep Learning ND:

1. Section 3: Convolutional Neural Networks - Lesson 6: Style Transfer finished

Computer Vision ND:

1. Worked on the Project 1: Facial Keypoint Detection

Day 42: 10/20/2019.

Deep Learning ND:

1. Worked on the Project 2: Dog-Breed Classifier

Day 43: 10/21/2019.

Deep Learning ND:

1. Worked on the Project 2: Dog-Breed Classifier

(I forgot to send it yesterday night.) Today's encouragement goes to @EvaK , @BabatundeO , @Richárd ÁdámV , @ZsoltB !

Day 44: 10/22/2019.

Deep Learning ND:

1. Section 3: Convolutional Neural Networks - Lesson 8: Deep Learning for Cancer Detections Concepts 1-15 finished

Today's encouragement goes to @Paul BruceS , @KonstantinosK , @DishinG , @FlorentG !

Day 45: 10/23/2019.

Computer Vision ND:

1. Worked on the Project 1: Facial Keypoint Detection (I forgot to send the report yesterday night.)

Day 46: 10/24/2019.

Computer Vision ND:

1. Worked on the Project 1: Facial Keypoint Detection
2. I'd like to encourage @Jacqueline SusanM , @ZsoltB , @HelenaB , @FridaR to keep going!

Day 47: 10/25/2019.

Computer Vision ND:

1. Worked on the Project 1: Facial Keypoint Detection

Day 48: 10/26/2019.

Deep Learning ND:

1. Worked on the Project 2: Dog-Breed Classifier

Day off: 10/27/2019.

Day 49: 10/28/2019.

Deep Learning ND:

1. Worked on the Project 2: Dog-Breed Classifier

Computer Vision ND:

1. Read the Namish paper: https://arxiv.org/pdf/1710.00977.pdf
2. Worked on the Project 1: Facial Keypoint Detection

Today's encouragement goes to: @joeH , @AnkitV , @NomanA !

Day 50: 10/29/2019.

Computer Vision ND:

1. Worked on the Project 1: Facial Keypoint Detection

(Due to internet connection error to Student Hub, I was unable to post the yesterday's log.)

Day 51: 10/30/2019.

Computer Vision ND:

1. Worked on the Project 1: Facial Keypoint Detection

Day 52: 10/31/2019.

Computer Vision ND:

1. Worked on the Project 1: Facial Keypoint Detection

Day 53: 11/01/2019.

Today I’m practicing how to work with Cascade classifier. #PracticeMakesPerfect

Deep Learning ND:

1. I went through this tutorial: https://docs.opencv.org/trunk/db/d28/tutorial_cascade_classifier.html
2. Worked on the Project 2: Dog-Breed Classifier

Day 54: 11/02/2019.

Today I’m practicing how to do classification. #PracticeMakesPerfect

Deep Learning ND:

1. Worked on the Project 2: Dog-Breed Classifier
2. I went through the PyTorch Chatbot Tutorial and played a littlebit with the chatbot. Today I'd like to encourage @Paul BruceS , @KonstantinosK , @DishinG , @FlorentG, @Jacqueline SusanM , @ZsoltB , @HelenaB , @FridaR !

Day 55: 11/03/2019.

Today I’m practicing how to do classification. #PracticeMakesPerfect

Deep Learning ND:

1. I continued to work on the Project 2: Dog-Breed Classifier

Day 56: 11/04/2019.

Worked on both project (Facial Keypoint and Dog-breed classification) in Colab.

Day 57: 11/05/2019.

Computer Vision ND:

1. Section 3: Advanced Computer Vision & Deep Learning - Lesson 1: Advanced CNN Architectures Concepts 1-6 completed

Day 58: 11/06/2019.

Deep Learning ND:

1. Worked on the Project 2: Dog-Breed Classifier

Day 59: 11/07/2019.

1. Worked on both project (Facial Keypoint and Dog-breed classification) in Colab.

Day 60: 11/08/2019.

Computer Vision ND:

1. Section 1: Introduction to Computer Vision - Lesson 10: Jobs in Computer Vision finished.

Yesterday I forgot to post my log. I encourage @AhmedT , @ZsoltB .

Day 61: 11/09/2019.

Computer Vision ND:

1. I've read a post about self driving car by David Silver: https://www.linkedin.com/pulse/how-computer-vision-works-self-driving-cars-david-silver/
2. And I have watched his TEDx Talk: https://www.youtube.com/watch?v=Ly92UcnoESMYS
3. Section 2: Optional: Cloud Computing - Lesson 1: Cloud computing with Google Cloud Concepts 1-4 finished

Day off: 11/10/2019.

Day 62: 11/11/2019.

Deep Learning ND:

1. Section 3. Convolutional Neural Networks - Lesson 9: Jobs in Deep Learning finished.
2. Lesson 10 Project - Optimize your Github profile - Concepts 1-9 finished

Day 63: 11/12/2019.

Deep Learning ND:

1. Worked on the Project 2: Dog-Breed Classifier

Day 64: 11/13/2019.

Deep Learning ND:

1. Worked on my GitHub profile: made new repository from the first project
2. Today I'd like to encourage @LauraT , @FuzhanR , @Paul BruceS , @Jacqueline SusanM , @ZsoltB , @HelenaB , @FridaR

Computer Vision ND:

1. Section 2: Optional: Cloud Computing - Lesson 1: Cloud computing with Google Cloud Concepts finished
2. Section 2: Optional: Cloud Computing - Lesson 2: Cloud computing with AWS finished

Day 65: 11/14/2019.

Computer Vision ND:

1. Worked on the project
2. Lesson 10 Project - Optimize your Github profile - Concepts 9-10 finished
3. Writing READMEs course (https://classroom.udacity.com/courses/ud777) finished

Deep Learning ND:

1. Worked on the project