├── Computer-Vision-with-TensorFlow ├── Classification_with_Keras.ipynb ├── Image-Classification-with-TensorFlow-2-x.ipynb ├── Introduction-to-CNN.ipynb ├── MNIST-with-TensorFlow.ipynb ├── Pratical_Image_Classification_with_Keras.ipynb ├── Preparing-Image-Data-with-Tensorflow-2-x.ipynb ├── Rock-Paper-Scissors-with-Tensorflow.ipynb └── horses-vs-humans-with-tensorflow.ipynb ├── Data ├── jena_climate_2009_2016.csv ├── ridership.tgz ├── ridership │ └── CTA_-_Ridership_-_Daily_Boarding_Totals.csv └── tinyshakespeare.txt ├── Images └── Deep-Learning-with-TensorFlow.png ├── NLP-with-TensorFlow ├── Bag-of-Words.ipynb ├── Generating-Text-using-a-Character-RNN-Model.ipynb ├── Hands-on-Word-Embeddings.ipynb ├── Intro-to-Word-Embedding.ipynb ├── Introduction-to-NLP.ipynb ├── Sentiment-Analysis-with-TensorFlow-Hub.ipynb ├── Sentiment-Analysis.ipynb ├── Sentiment_Analysis_with_TensorFlow.ipynb ├── Text-Classifiacation-with-HF-and-TF.ipynb └── TextVectorization-TensorFlow.ipynb ├── Pratical-Keras-Tutorials ├── ANN-with-Scikit-Learn.ipynb ├── Hands_on_Keras_Functional_API.ipynb ├── How_to_Use_Keras_Functional_API.ipynb ├── Improving_Model_Accuracy.ipynb ├── Keras_Custom_Layer.ipynb ├── Keras_Tuner.ipynb ├── Model_Subclassing_with_Keras.ipynb ├── Pratical-Keras-Custom-Layer.ipynb ├── Pratical_Image_Classification_with_Keras.ipynb ├── Pratical_Keras_Functional_API.ipynb ├── Pratical_Keras_Subclassing_Model.ipynb ├── Preparing-Tabular-Data-with-Tensorflow.ipynb └── Save_and_load_models.ipynb ├── README.md ├── TensorFlow-Ecosystem ├── How to Use Data Pipelines with Python.ipynb ├── Intro-to-TensorFlow.ipynb ├── TFDS.ipynb ├── TensorFlow_Tutorial.ipynb └── tf-data-Dataset.ipynb ├── Time-Series ├── Introduction-to-Time-Series.ipynb ├── ML-Approach-for-Time-Series.ipynb ├── Multivariate-Time-Series-Analysis.ipynb ├── RNN-with-NumPy.ipynb ├── Time-Series-for-Deep-Learning.ipynb └── Univariate-Time-Series-Analysis.ipynb └── Transfer-Learning ├── 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