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Deep Learning Master Class

1,499.00

Description

What will you learn?

Section 1: Course Overview

✅ DAY–1 Introduction to Deep Learning

✅ DAY–2 Basic Computer Vision

Section 2: Artificial Neural Network

✅ DAY–3 Neurons & Perceptron

✅ DAY–4 Activation Function

✅ DAY–5 Gradient Descent

✅ DAY – 6 Stochastic Gradient Descent

✅ DAY – 7 Backpropagation

✅ DAY – 8 Artificial Neural Network – Project 1

Section 3: Deep Neural Network

✅ DAY – 9 Optimization Algorithms – SGD, Momentum, NAG, Adagrad, Adadelta , RMSprop, Adam

✅ DAY – 10 Batch Normalization

✅ DAY– 11 Hyperparameter tuning

✅ DAY– 12 Interpretability

✅ DAY– 13 Deep Neural Network – Project 2

Section 4: Convolutional Neural Network

✅ DAY– 14 Convolutional Neural Network & its Layers

✅ DAY– 15 CNN Architecture

✅ Day–16 Different frameworks on Deep Learning (Tensorflow, Keras, PyTorch & Caffe)

✅ Day-17 Object Recognition using Pre Trained Model – Caffe – Project 3

✅ Day-18 Image classification using Convolutional Neural Network from Scratch – Tensorflow & Keras – Project 4

✅ Day-19 Custom Image Classification using Transfer Learning – Project 5

✅ Day-20 YOLO Object recognition – Project 6

✅ Day 21 Image Segmentation – Project 7

✅ Day 22 Project using MxNet – Project 8

✅ Day 23 Project using PyTorch – Project 9

✅ Day 24 Social Distancing detector – Project 10

✅ Day 25 Face Mask detector – Project 11

Section 5: Recurrent Neural Network

✅ Day 26 Introduction to RNN and LSTM

✅ Day 27 Project using RNN – Project 12

Section 6:

✅ Day 28 Introduction CUDA Toolkit and cuDNN for deep learning

✅ Day 29 Getting started with the Intel Movidius Neural Compute Stick – Project 13

✅ Day 30 Custom Object classification using Nvidia Jetson – Project 15

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