Duration & Time
- Date will be updated soon...
- 10 hours (2 hours daily)
- 6:00 PM to 8:00 PM
Delivery Mode
- Online interactive session on zoom
Course Content
Introduction of Machine Learning /Deep learning and Artificial Intelligent
- Introduction of Artificial Intelligence and Machine Learning
- A brief introduction to Machine Learning for AI
- Introduction of DeepLearning
- Difference between Machine Learning and DeepLearning
- DeepLearning Techniques
- Types of Learning
- DeepLearning System Design
- Supervised Learning- Regression
- Classification
- Future scope, Machine / Deep Learning, And Artificial Intelligence
Python/Anaconda
- Introduction to python and anaconda
- Conditional Statements
- Looping, Control Statements
- Lists, Tuple, Dictionaries
- String Manipulation
- Functions
- Installing Packages
- Introduction of Various Tool
- Introduction of Anaconda
- Working on spyder, Jupyter notebook
Introduction of Deep Learning Algorithms
- Gradient Descent
- Perceptrons
- Neural Network
- RNN
- LSTM/GRU
- CNN
- DBN
- DNS
- Application of Various Deep Learning Algorithms
Neural Network
- BASIC introduction Neuron
- The Neuron Diagram
- Neuron Models
- Activation function
- Binary Step Function
- Linear Function
- Sigmoid
- Tanh
- RELU
- Leaky ReLU
- Softmax
- single-layer feed-forward
- multi-layer feed-forward
- Feedforward Neural Networks
CNN
- Convolutional Neural Network (CNN)
- What is CNN?
- CNN Architecture
- Convolution
- Pooling and Stride
- AlexNet
- GoogLeNet
- VGGNet
- MobileNets
- ResNet
TensorFlow
- Introduction of TensorFlow
- Basics of TensorFlow
- Graph in TensorFlow
- TensorFlow Session
- Placeholders, Constants, Variables
- Common Data Stored in Tensors
- Introduction of Keras and implementation
Project (Demo)
- MNIST Handwritten Digits Dataset
- CIFAR Image Dataset
- Image Classification Using CIFAR-10 Dataset
- Human Face Detection
- Drowsy Driver Detection System
- Gender Recognition Using Voice
- Human Pose Detection
- Hand Gesture Recognition System
- Facial Expression Recognition Project
- Linear Regression with TensorFlow
- Logistic Regression using TensorFlow
- Images classification Using TensorFlow
- Object Recognition Using Convolutional Neural Networks
- Object tracking using CNN
- Face recognition using CNN
Certification
A certificate of completion will be provided to all registered attendees.