Hi! This repo contains my implementation of Notebook's from Deep learning Specialization from deeplearning.ai by Andrew Ng.

Course 1 - Neural Network and Deeplearning.

https://www.coursera.org/learn/neural-networks-deep-learning Paper's/Notes Referred :

Week2 -

• Implementing a Neural Network from Scratch in Python – An Introduction (Denny Britz, 2015)
• Why normalize images by subtracting dataset's image mean, instead of the current image mean in deep learning? (Stack Exchange)

Week3 -

• Demystifying Deep Convolutional Neural Networks (Adam Harley)
• CS231n: Convolutional Neural Networks for Visual Recognition (Stanford University)

Week4 -

• Autoreload of modules in IPython (Stack Overflow)

Course 2 - Improving Deep Neural Networks

https://www.coursera.org/learn/deep-neural-network Paper's/Note's Referred:

• Introduction to gradients and automatic differentiation (TensorFlow Documentation)
• tf.GradientTape (TensorFlow Documentation)

Course 3 - Structuring Machine learning Projects

https://www.coursera.org/learn/machine-learning-projects/home/welcome Paper's/Note's Refered :

• None.

Course 4 - Convolutional Neural Network

https://www.coursera.org/learn/convolutional-neural-networks Paper's/Note's Referred:

Week1-

• The Sequential model (TensorFlow Documentation)
• The Functional API (TensorFlow Documentation)

Week2-

• Deep Residual Learning for Image Recognition (He, Zhang, Ren & Sun, 2015)
• d​eep-learning-models/resnet50.py/ (GitHub: fchollet)
• MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications (Howard, Zhu, Chen, Kalenichenko, Wang, Weyand, Andreetto, ​& Adam, 2017)
• MobileNetV2: Inverted Residuals and Linear Bottlenecks (Sandler, Howard, Zhu, Zhmoginov &Chen, 2018)
• EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks (Tan & Le, 2019)

Week3-

• You Only Look Once: Unified, Real-Time Object Detection (Redmon, Divvala, Girshick & Farhadi, 2015)
• YOLO9000: Better, Faster, Stronger (Redmon & Farhadi, 2016)
• YAD2K (GitHub: allanzelener)
• YOLO: Real-Time Object Detection
• Fully Convolutional Architectures for Multi-Class Segmentation in Chest Radiographs (Novikov, Lenis, Major, Hladůvka, Wimmer & Bühler, 2017)
• Automatic Brain Tumor Detection and Segmentation Using U-Net Based Fully Convolutional Networks (Dong, Yang, Liu, Mo & Guo, 2017)
• U-Net: Convolutional Networks for Biomedical Image Segmentation (Ronneberger, Fischer & Brox, 2015)

Week4-

• FaceNet: A Unified Embedding for Face Recognition and Clustering (Schroff, Kalenichenko & Philbin, 2015)
• DeepFace: Closing the Gap to Human-Level Performance in Face Verification (Taigman, Yang, Ranzato & Wolf)
• f​acenet (GitHub: davidsandberg)
• How to Develop a Face Recognition System Using FaceNet in Keras (Jason Brownlee, 2019)
• k​eras-facenet/notebook/tf_to_keras.ipynb (GitHub: nyoki-mtl)
• A Neural Algorithm of Artistic Style (Gatys, Ecker & Bethge, 2015)
• Convolutional neural networks for artistic style transfer
• TensorFlow Implementation of "A Neural Algorithm of Artistic Style"
• V​ery Deep Convolutional Networks For Large-Scale Image Recognition (Simonyan & Zisserman, 2015)
• Pretrained models (MatConvNet)

Course 5 : Sequential Model

https://www.coursera.org/learn/nlp-sequence-models/home/welcome Paper's/Note's Referred:

Week 1:

• Minimal character-level language model with a Vanilla Recurrent Neural Network, in Python/numpy (GitHub: karpathy)
• The Unreasonable Effectiveness of Recurrent Neural Networks (Andrej Karpathy blog, 2015)
• d​eepjazz (GitHub: jisungk)
• Learning Jazz Grammars (Gillick, Tang & Keller, 2010)
• A Grammatical Approach to Automatic Improvisation (Keller & Morrison, 2007)
• Surprising Harmonies (Pachet, 1999)

Week 2:

• Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings (Bolukbasi, Chang, Zou, Saligrama​ & Kalai, 2016)
• GloVe: Global Vectors for Word Representation (Pennington, Socher & Manning, 2014)
• W​oebot.

Week 4:

• Natural Language Processing Specialization (by DeepLearning.AI)
• Attention Is All You Need (Vaswani, Shazeer, Parmar, Uszkoreit, Jones, Gomez, Kaiser​ & Polosukhin, 2017)