ZakiKurdya / Tensorflow-Developer

Let's crack the Google Certified Tensorflow Developer exam together!

Tensorflow Developer

Let's become a Google Certified Tensorflow Developer together !

file structure

.
├── 1.\ Introduction\ to\ TensorFlow\ for\ Artificial\ Intelligence,\ Machine\ Learning,\ and\ Deep\ Learning
│   ├── A\ Computer\ Vision\ Example.ipynb
│   ├── Convolution.py
│   ├── Excercise-3-Convolution.ipynb
│   ├── Exercise\ 1\ (Housing\ Prices).md
│   ├── Exercise2-callback\ handwriting.ipynb
│   ├── Exercise4-Question.ipynb
│   ├── Exercise_1_House_Prices_Question.ipynb
│   ├── README.md
│   ├── Walk\ through\ Call\ back.ipynb
│   ├── Week1\ Quiz.md
│   ├── Week2\ Quiz.md
│   ├── Week3\ Quiz.md
│   ├── code&note.py
│   ├── hourse_human_withValidation.ipynb
│   ├── resources
│   └── week4\ Quiz.md
├── 2.\ Convolutional\ Neural\ Networks\ in\ Tensorflow
│   ├── README.md
│   ├── course_2_part_2_lesson_2_notebook.py
│   ├── resources
│   └── tmp
├── 3.\ Natural\ Language\ Processing\ in\ TensorFlow
│   ├── 1.\ Tokenizer.py
│   ├── 2.BBC\ news\ archive.py
│   ├── 3.\ IMDB\ Subwords\ 8K\ with\ Multi\ Layer\ LSTM.py
│   ├── 4.\ week_4_lesson_1_notebook(\ predict\ next\ words).py
│   ├── 5.\ week_4_lesson_2_(write\ a\ poem).py
│   ├── 6.\ nlp_week4_shakespeare.py
│   ├── README.md
│   └── tmp
├── 4.\ Sequences,\ Time\ Series\ and\ Prediction
│   ├── 1.\ Naive\ Forecast.py
│   ├── 10.LSTM-(batch).py
│   ├── 11.SunSpot_conv_lstm.py
│   ├── 12.temperatures_conv_lstm_lambda.py
│   ├── 2.\ Create\ and\ predict\ synthetic\ data.py
│   ├── 3.Preparing\ features\ and\ labels.py
│   ├── 4.Single\ layer\ neural\ network\ notebook.py
│   ├── 5.Deep\ neural\ network\ notebook.ipynb
│   ├── 5.DeepNeuralNetwork.py
│   ├── 6.Predict\ with\ DNN.py
│   ├── 7.RNN.py
│   ├── 8.\ LSTM.ipynb
│   ├── 8.\ LSTM.py
│   ├── 9.\ MAE.ipynb
│   ├── 9.\ MAE.py
│   ├── DNN-playground.ipynb
│   ├── README.md
│   ├── a\ few\ scenarios\ for\ time\ series.ipynb
│   ├── code&note.py
│   ├── math\ forecasting.ipynb
│   ├── real-world\ time\ series\ prediction-DNN.ipynb
│   ├── real-world\ time\ series\ prediction.ipynb
│   ├── tmp
│   └── tst.csv
├── LICENSE
├── README.md
├── Setting_Up_TF_Developer_Certificate_Exam.pdf
├── TF_Certificate_Candidate_Handbook.pdf
├── test.py
└── tree.txt

9 directories, 53 files