Overview

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Embark on a comprehensive 14-hour deep learning journey, mastering TensorFlow 2.0, Keras, and Python from scratch. Explore neural networks, convolutional neural networks (CNNs), and recurrent neural networks (RNNs) through hands-on tutorials. Learn essential concepts like activation functions, loss functions, and gradient descent. Dive into practical applications including image classification, object detection, and natural language processing. Discover advanced topics such as transfer learning, YOLO algorithm, LSTM, GRU, and BERT. Gain proficiency in optimizing deep learning models, implementing word embeddings, and utilizing TensorFlow's input pipeline. By the end, you'll be equipped to tackle real-world machine learning challenges and deploy models using TensorFlow Serving.

Syllabus

Introduction | Deep Learning Tutorial 1 (Tensorflow Tutorial, Keras & Python).
Why deep learning is becoming so popular? | Deep Learning Tutorial 2 (Tensorflow2.0, Keras & Python).
What is a neuron? | Deep Learning Tutorial 3 (Tensorflow Tutorial, Keras & Python).
What is a Neural Network | Deep Learning Tutorial 4 (Tensorflow2.0, Keras & Python).
Install tensorflow 2.0 | Deep Learning Tutorial 5 (Tensorflow Tutorial, Keras & Python).
Pytorch vs Tensorflow vs Keras | Deep Learning Tutorial 6 (Tensorflow Tutorial, Keras & Python).
Neural Network For Handwritten Digits Classification | Deep Learning Tutorial 7 (Tensorflow2.0).
Activation Functions | Deep Learning Tutorial 8 (Tensorflow Tutorial, Keras & Python).
Derivatives | Deep Learning Tutorial 9 (Tensorflow Tutorial, Keras & Python).
Matrix Basics | Deep Learning Tutorial 10 (Tensorflow Tutorial, Keras & Python).
Loss or Cost Function | Deep Learning Tutorial 11 (Tensorflow Tutorial, Keras & Python).
Gradient Descent For Neural Network | Deep Learning Tutorial 12 (Tensorflow2.0, Keras & Python).
Implement Neural Network In Python | Deep Learning Tutorial 13 (Tensorflow2.0, Keras & Python).
Stochastic Gradient Descent vs Batch Gradient Descent vs Mini Batch Gradient Descent |DL Tutorial 14.
Chain Rule | Deep Learning Tutorial 15 (Tensorflow2.0, Keras & Python).
Tensorboard Introduction | Deep Learning Tutorial 16 (Tensorflow2.0, Keras & Python).
GPU bench-marking with image classification | Deep Learning Tutorial 17 (Tensorflow2.0, Python).
Customer churn prediction using ANN | Deep Learning Tutorial 18 (Tensorflow2.0, Keras & Python).
Precision, Recall, F1 score, True Positive|Deep Learning Tutorial 19 (Tensorflow2.0, Keras & Python).
Dropout Regularization | Deep Learning Tutorial 20 (Tensorflow2.0, Keras & Python).
Handling imbalanced dataset in machine learning | Deep Learning Tutorial 21 (Tensorflow2.0 & Python).
Applications of computer vision | Deep Learning Tutorial 22 (Tensorflow2.0, Keras & Python).
Simple explanation of convolutional neural network | Deep Learning Tutorial 23 (Tensorflow & Python).
Image classification using CNN (CIFAR10 dataset) | Deep Learning Tutorial 24 (Tensorflow & Python).
Convolution padding and stride | Deep Learning Tutorial 25 (Tensorflow2.0, Keras & Python).
Data augmentation to address overfitting | Deep Learning Tutorial 26 (Tensorflow, Keras & Python).
Transfer Learning | Deep Learning Tutorial 27 (Tensorflow, Keras & Python).
Image classification vs Object detection vs Image Segmentation | Deep Learning Tutorial 28.
Popular datasets for computer vision: ImageNet, Coco and Google Open images | Deep Learning 29.
Sliding Window Object Detection | Deep Learning Tutorial 30 (Tensorflow, Keras & Python).
What is YOLO algorithm? | Deep Learning Tutorial 31 (Tensorflow, Keras & Python).
Object detection using YOLO v4 and pre trained model | Deep Learning Tutorial 32 (Tensorflow).
What is Recurrent Neural Network (RNN)? Deep Learning Tutorial 33 (Tensorflow, Keras & Python).
Types of RNN | Recurrent Neural Network Types | Deep Learning Tutorial 34 (Tensorflow & Python).
Vanishing and exploding gradients | Deep Learning Tutorial 35 (Tensorflow, Keras & Python).
Simple Explanation of LSTM | Deep Learning Tutorial 36 (Tensorflow, Keras & Python).
Simple Explanation of GRU (Gated Recurrent Units) | Deep Learning Tutorial 37 (Tensorflow & Python).
Bidirectional RNN | Deep Learning Tutorial 38 (Tensorflow, Keras & Python).
Converting words to numbers, Word Embeddings | Deep Learning Tutorial 39 (Tensorflow & Python).
Word embedding using keras embedding layer | Deep Learning Tutorial 40 (Tensorflow, Keras & Python).
What is Word2Vec? A Simple Explanation | Deep Learning Tutorial 41 (Tensorflow, Keras & Python).
Word2Vec Part 2 | Implement word2vec in gensim | | Deep Learning Tutorial 42 with Python.
Distributed Training On NVIDIA DGX Station A100 | Deep Learning Tutorial 43 (Tensorflow & Python).
Tensorflow Input Pipeline | tf Dataset | Deep Learning Tutorial 44 (Tensorflow, Keras & Python).
Optimize Tensorflow Pipeline Performance: prefetch & cache | Deep Learning Tutorial 45 (Tensorflow).
What is BERT? | Deep Learning Tutorial 46 (Tensorflow, Keras & Python).
Text Classification Using BERT & Tensorflow | Deep Learning Tutorial 47 (Tensorflow, Keras & Python).
tf serving tutorial | tensorflow serving tutorial | Deep Learning Tutorial 48 (Tensorflow, Python).
Quantization in deep learning | Deep Learning Tutorial 49 (Tensorflow, Keras & Python).