QUICK ENQUIRY
ARTIFICIAL INTELLIGENCE
MACHINE LEARNING
PYTHON-20 HRS
MACHINE LEARNING-40 HRS
DEEP LEARNING-20HRS
SYLLABUS
What is Machine Learning
Crash Course of Python Programming
Getting Started with Linux environment
Computer vision and image processing basics
- Loading, Displaying and saving Images.
- Drawing Operations.
- Basic Image Processing
- Kernels
- Morphological Operations
- Smoothing & blurring
- Thresholding
- Gradient &Edge Detection
- Contours
- Histograms
Image descriptors
- Color Channel Statistics
- Color Histograms
- Haralick Texture
- Local Binary Patterns
- HOG
- Key Point detection
Image classification and machine learning algorithms
- K-Nearest Neighbors
- Logistic Regression
- Support Vector Machines
- Decision Trees
- Random Forest
- K means Clustering
Computer Vision cases studies
- Object tracking in video
- Human detection
- Face detection and recognition
- Drowsiness Detection
- OCR
- Text Segmentation
- Sound Analysis
- And much more…
Introduction to Deep Learning.
- Machine learning Algorithms and primer
- Why Deep learning is becoming so popular?
- Introduction to Deep Neural Networks
- Sneak peek into open source python libraries
Convolution Neural Network
- The perception Algorithm
- Multi-layer Network
- Develop your first neural network using keras
- Diving deep in to Convolution Neural Network – CNN Primer
- It is all about dataset!! And How to gather them
- Training your own CNN (Shallow network) for Mnist Dataset
- Training a Very deep CNN for Mnist Dataset
- Improving Model Performance with Image Augmentation
- Object Detection using CNN for CIFAR 10 dataset
CNN Architechures
- Implementing CNN Architechures
- LeNet
- KarpathyNet
- MiniVGGNet
- Over Feat Framework
ImageNet architechures
- State of the art ImageNet algorithms
- Flower 17 Classification using
- VGG16
- VGG19
- Inception-v3
- ResNet50
- Inception_Resnet_V2
- Squeeze net CNN a simplified model for remote processor
Case Study
- Case Study 1 - Emotion Detection
- Case Study 2 - Age and gender Detection
- Case Study 3 - Car Model Identification
- Case Study 4 – Object Detection and much more.
Week end training
Batch 1 : 3rd August 2019
Batch 2 : 10th August 2019
