Tensorflow Deep Learing Fundamentals

I started to studying for the Tensorflow Certificate seriously in 30th July 2021 (honestly, i started in 15th but i was busy studying for final semester exam in my University), and I took the exam in 29th August 2021. I was very nervous but don't worry, you can do it too.

頑張ってね。

📝 Repository learning Tensorflow and reparing for Tensorflow Certificate exam

My study routine:

• I spend about 2 days to studying each module.
• Beside notebook, read book and watch online lecture to understand the concept underlying the code.
• Working with preprocess data and fine tune hyperparameters beside the building models.
• Fix bugs, yes, there are lots of bugs when i coded like dimension error, versions error, etc.

My development environment:

• Google colab (thanks google for offer free GPU 🙏).
• Pycharm (recommend because the Exam use PyCharm IDE).
• ...

About the notebook environment when i was created:

• Python == 3.8.x
• Tensorflow == 2.5.x

If you run these on collab, the environment or some TensorFlow module will be a little bit different.

Basic Intuition

Math

• ML Cheatsheet: Calculus
• ML Cheatsheet: Linear Algebra
• Probability Cheatsheet
• ML Cheatsheet: Math notation

ANN

• ML Cheatsheet: ANN
• 3Blue1Brown: ANN - playlist
• Neural Network Simulator

Number	Notebook	Description	Extras
00	Tensorflow Fundamentals	Basic tensor operations	Machine Learing & Deep Learning , Karpathy's Blog
01	TensorFlow Regression	Introduce to simple linear regression problems	Gradient Descent demo , Backpropagation from scrath
02	TensorFlow Classification	Simple binary classification and multiple classification	Activation Function cheatsheet
03	TensorFlow Computer Vision	Solve image classification with CNN	CNN explainer
04	Transfer Learning: Feature Extraction	Use Transfer Learning, specifically Feature Extraction for our own problem.	Transfer learning
05	Transfer Learning: Fine Tune	Use Transfer Learning, Fine Tuning.
06	Transfer Learning: Scalling Up	Use Transfer Learning for the 101 classes Food101 dataset
07	Mile Stone Project 1: FoodVision	Introduce to Mixed Precision and combine all what i have learned
08	TensorFlow NLP Fundamentals	Introduce to simple NLP problems like Twitter Disaster dataset	Word Embedding , Word2Vec , GloVe embeddings , Chirs Olah intro to LSTM
09	Milestone Project 2: SkimLit	NLP classification, make Medical Abstraction easier to read using PubMed 200k RCT dataset
10	TensorFlow Time Series Fundamentals & Milestone Project 3: BitPredict	Introduce to Time series problems and try create a failed bitcoin price prediction	Uber forcasting introduction , Forecasting priciples and practices , How (not) to use the ML for time series forcasting
11	Tensorflow Skill Checklist	Skill checklist according to TensorFlow candidate handbook	TensorFlow Certificate Handbook

Acknowledge:

1. Thanks mrdbourke for provide a brilliant course, help me when i was stuck with errors.
2. Thanks Kaggle for give me a flatform to take part in competition to challenges what i've learned.
3. Thanks MIT for provide a whole series lectures online about ANN.
4. And thanks myself for not giving up. 🤣