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AI with Machine Learning and Deep Learning represents the integration of data-driven, learning-based techniques into artificial intelligence systems, enabling them to perform complex tasks and make intelligent decisions across various domains and industries.
Curriculum Designed by Experts
Introduction with Artificial Intelligence
ML and other related terms to AI
A working example of AI and ML
Project 1 – These simple tasks are to make you understand how AI and ML can find their applications in real life.
Python libraries for ML
Setting up Anaconda development environment
Getting into core development of ML
These simple tasks are going to give you some great experience with Machine Learning introductory programs or better say, “Hello world” programs of Machine Learning.
Different ML techniques
Developing complete project of ML (IRIS flower project)
After completing these project, you have done and understood multiple complete projects of Machine Learning.
Introduction of Ai with Deep Learning
PyTorch Fundamentals : Matrices
PyTorch Fundamentals : Variables and Gradients
Linear Regression with PyTorch
Logistic Regression with PyTorch
Feedforward Neural Network with PyTorch
Convolutional Neural Network (CNN) with PyTorch
Recurrent Neural Networks (RNN)
Long Short-Term Memory Networks (LSTM)
Deep Learning Projects
Churn Modelling using ANN | Mini |
Image Classification | Mini |
Image classification using Transfer learning | Major |
Sentence Classification using RNN,LSTM,GRU | Mini |
Sentence Classification using word embeddings | Major |
Object Detection using yolo | Major |
Machine Learning Projects
EDA on movies database | Mini |
House price prediction using Regression | Mini |
Predict survival on the Titanic using Classification | Mini |
Image Clustering | Mini |
Document Clustering | Mini |
Twitter US Airline Sentiment | Major |
Restaurant revenue prediction | Major |
Disease Prediction | Major |
Note : Depends upon Trainers above projects may vary