Artificial Intelligence Training in Chennai

Artificial Intelligence Training in Chennai

What is Artificial Intelligence?

Artificial Intelligence is being there in the industry for a long time.  What makes it more popular now? Why all the top-notch companies like Google, Intel, suddenly started to invest on AI.


Because of the usage of Powerful learning technique so called Machine and Deep Learning. This technique has transformed the AI which was weaker before into stronger AI.


What makes it more powerful?  It uses simplified learning technique that can learn and improve on it own from experience with less user intervention which makes life comfortable by making the machine think, do , react like the humans do.


Autonomous cars, google’s latest android P beta, amazon go (just go shopping), Facebook’s funny chat bots and much more have banging the market to the core, which makes users(that is us) experience the way they never had.


Using Machine and Deep learning algorithms Literally all the process can be automated and can also give a personal touch like the humans do.


Difference between Machine learning and Deep Learning?

Machine learning is the base architechure for all, which uses handcrafted feature extraction techniques and learning algorithms, where as in deep learning the introduction of Neural network and usage of Nvidia GPU makes it more powerful with consumption of huge dataset whereas in machine learning doesnt need huge dataset to achieve feet.


If you don’t have idea about artificial intelligence take training from Artificial Intelligence Training in Chennai


Artificial Intelligence with Machine Learning Course Syllabus:

1. What is Machine Learning
2. Crash Course of Python Programming
3. Getting Started with Linux environment
4. Computer vision and image processing basics

  • Loading, Displaying and saving Images.
  • Drawing Operations.
  • Basic Image Processing
  • Kernals
  • Morphological Operations
  • Smoothing & blurring
  • Thresholding
  • Gradient &Edge Detection
  • Contours
  • Histograms

5. Image descriptors

  • Color Channel Statistics
  • Color Histograms
  • Haralick Texture
  • Local Binary Patterns
  • HOG
  • Key Point detection

6. Image classification and machine learning algorithms

  • K-Nearest Neighbors
  • Logistic Regression
  • Support Vector Machines
  • Decision Trees
  • Random Forest
  • K means Clustering

7. Computer Vision cases studies

  • Object tracking in video
  • Human detection
  • Face detection and recognition
  • Plant classification
  • Distance measurement
  • Drowsiness Detection
  • OCR
  • Automatic License Plate Detection
  • Sound Analysis
  • And much more…

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