DeepLearning.AI-TensorFlow-Developer-Professional-Certificate

Instructed by Laurence Moroney

Offered by

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About this Professional Certificate

Welcome! This repository is a collection of the work I completed while earning the TensorFlow Developer Professional Certificate from DeepLearning.AI.

Throughout the course, I gained hands-on experience in building and training deep learning models using TensorFlow 2.x and Keras. The program covered key areas such as computer vision, natural language processing, and time series forecasting. I explored different types of neural networks, including CNNs, GRUs, and LSTMs, and learned how to apply them to real-world problems.

Along the way, I also developed a solid understanding of:

• Optimization techniques like Adam, SGD, and RMSprop
• Regularization strategies such as L1/L2 and Dropout
• Data preprocessing and augmentation
• Batch normalization and callbacks
• Loss functions, evaluation metrics, and sequential model design

This course was a deep dive into the world of deep learning, offering both theoretical knowledge and practical experience. It helped me build a strong foundation in TensorFlow and gave me the tools to train effective models for a variety of AI tasks.

Feel free to browse through the projects and practice exercises I've shared here. Hope you find them useful!

Please, check Coursera Honor Code before you take a look at the assignments.

For more you can check course info.

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Courses and Certificates

• Course 1 - Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

  • Week 1 - A New Programming Paradigm

    • Assigment:

      • Housing Prices: C1W1_Assignment.ipynb

    • Ungraded Labs:

      • Hello World Neural Network: C1_W1_Lab_1_hello_world_nn.ipynb

    • Quiz:

      • Quiz

  • Week 2 - Introduction to Computer Vision

    • Assigment:

      • Handwriting Recognition: C1W2_Assignment.ipynb

    • Ungraded Labs:

      • Beyond Hello World, A Computer Vision Example: C1_W2_Lab_1_beyond_hello_world.ipynb
      • Callbacks: C1_W2_Lab_2_callbacks.ipynb

    • Quiz:

      • Quiz

  • Week 3 - Enhancing Vision with Convolutional Neural Networks

    • Assigment:

      • Improve MNIST with Convolutions: C1W3_Assignment.ipynb

    • Ungraded Labs:

      • Improving Accuracy with Convolutions: C1_W3_Lab_1_improving_accuracy_using_convolutions.ipynb
      • Exploring Convolutions: C1_W3_Lab_2_exploring_convolutions.ipynb

    • Quiz:

      • Quiz

  • Week 4 - Using Real-world Images

    • Assigment:

      • Handling Complex Images: C1W4_Assignment.ipynb

    • Ungraded Labs:

      • Preprocessing Images to Train a Neural Network: C1_W4_Lab_1_image_data_preprocessing_no_validation.ipynb
      • Image Data Preprocessing with a Validation Set: C1_W4_Lab_2_image_data_preprocessing_with_validation.ipynb
      • Compacted Images: C1_W4_Lab_3_compacted_images.ipynb

    • Quiz:

      • Quiz
  Certificate

  

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• Course 2 - Convolutional Neural Networks in TensorFlow

  • Week 1 - Exploring a Large Dataset

    • Assigment:

      • Cats vs. Dogs: C2W1_Assignment.ipynb

    • Ungraded Labs:

      • Using more sophisticated images with Convolutional Neural Networks: C2_W1_Lab_1_cats_vs_dogs.ipynb

    • Quiz:

      • Quiz

  • Week 2 - Augmentation: A technique to avoid overfitting

    • Assigment:

      • Cats vs. Dogs using Augmentation: C2W2_Assignment.ipynb

    • Ungraded Labs:

      • Cats vs. Dogs with Augmentation: C2_W2_Lab_1_cats_v_dogs_augmentation.ipynb
      • Horses vs. Humans with Augmentation: C2_W2_Lab_2_horses_v_humans_augmentation.ipynb

    • Quiz:

      • Quiz

  • Week 3 - Transfer Learning

    • Assigment:

      • Horses vs. Humans using Transfer Learning: C2W3_Assignment.ipynb

    • Ungraded Labs:

      • Exploring Transfer Learning: C2_W3_Lab_1_transfer_learning.ipynb

    • Quiz:

      • Quiz

  • Week 4 - Multiclass Classifications

    • Assigment:

      • Multi-class Classifier: C2W4_Assignment.ipynb

    • Ungraded Labs:

      • Classifying Rock, Paper, and Scissors: C2_W4_Lab_1_multi_class_classifier.ipynb

    • Quiz:

      • Quiz
  Certificate

  

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• Course 3 - Natural Language Processing in TensorFlow

  • Week 1 - Sentiment in Text

    • Assigment:

      • Explore the BBC News Archive: C3W1_Assignment.ipynb

    • Ungraded Labs:

      • Building a Vocabulary: C3_W1_Lab_1_building_a_vocabulary.ipynb
      • Simple Sequences: C3_W1_Lab_2_sequences_basic.ipynb
      • Sarcasm: C3_W1_Lab_3_sarcasm.ipynb

    • Quiz:

      • Quiz

  • Week 2 - Word Embeddings

    • Assigment:

      • Categorizing the BBC News Archive: C3W2_Assignment.ipynb

    • Ungraded Labs:

      • Positive or Negative IMDB Reviews: C3_W2_Lab_1_imdb.ipynb
      • Sarcasm Classifier: C3_W2_Lab_2_sarcasm_classifier.ipynb
      • IMDB Review Subwords: C3_W2_Lab_3_imdb_subwords.ipynb

    • Quiz:

      • Quiz

  • Week 3 - Sequence Models

    • Assigment:

      • Exploring Overfitting in NLP: C3W3_Assignment.ipynb

    • Ungraded Labs:

      • IMDB Subwords with Single Layer LSTM: C3_W3_Lab_1_single_layer_LSTM.ipynb
      • IMDB Subwords with Multi Layer LSTM: C3_W3_Lab_2_multiple_layer_LSTM.ipynb
      • IMDB Subwords with 1D Convolutional Layer: C3_W3_Lab_3_Conv1D.ipynb
      • IMDB Reviews with GRU (and optional LSTM and Conv1D): C3_W3_Lab_4_imdb_reviews_with_GRU_LSTM_Conv1D.ipynb
      • Sarcasm with Bidirectional LSTM: C3_W3_Lab_5_sarcasm_with_bi_LSTM.ipynb
      • Sarcasm with 1D Convolutional Layer: C3_W3_Lab_6_sarcasm_with_1D_convolutional.ipynb

    • Quiz:

      • Quiz

  • Week 4 - Sequences Models and Literature

    • Assigment:

      • Writing Shakespeare with LSTMs: C3W4_Assignment.ipynb

    • Ungraded Labs:

      • NLP with Irish Music: C3_W4_Lab_1.ipynb
      • Generating Poetry from Irish Lyrics: C3_W4_Lab_2_irish_lyrics.ipynb
      • (Optional) Generating text using a character-based RNN: C3_W4_Lab_3_text_generation.ipynb

    • Quiz:

      • Quiz
  Certificate

  

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• Course 4 - Sequences, Time Series and Prediction

  • Week 1 - Sequences and Prediction

    • Assigment:

      • Create and Predict Synthetic Data: C4W1_Assignment.ipynb

    • Ungraded Labs:

      • Time Series: C4_W1_Lab_1_time_series.ipynb
      • Forecasting: C4_W1_Lab_2_forecasting.ipynb

    • Quiz:

      • Quiz

  • Week 2 - Deep Neural Networks for Time Series

    • Assigment:

      • Predict with a DNN: C4W2_Assignment.ipynb

    • Ungraded Labs:

      • Preparing Features and Labels: C4_W2_Lab_1_features_and_labels.ipynb
      • Single Layer Neural Network: C4_W2_Lab_2_single_layer_NN.ipynb
      • Deep Neural Network: C4_W2_Lab_3_deep_NN.ipynb

    • Quiz:

      • Quiz

  • Week 3 - Recurrent Neural Networks for Time Series

    • Assigment:

      • Using RNN's and LSTM's for time series: C4W3_Assignment.ipynb

    • Ungraded Labs:

      • Recurrent Neural Network (RNN): C4_W3_Lab_1_RNN.ipynb
      • Long Short-Term Memory (LSTM): C4_W3_Lab_2_LSTM.ipynb

    • Quiz:

      • Quiz

  • Week 4 - Real-World Time Serie Data

    • Assigment:

      • Daily Minimum Temperatures in Melbourne - Real Life Data: C4W4_Assignment.ipynb

    • Ungraded Labs:

      • Long Short-Term Memory (LSTM): C4_W4_Lab_1_LSTM.ipynb
      • Sunspots: C4_W4_Lab_2_Sunspots.ipynb
      • Sunspots - DNN Only: C4_W4_Lab_3_DNN_only.ipynb

    • Quiz:

      • Quiz
  Certificate

  

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Reference

DeepLearning.AI TensorFlow Developer Professional Certificate