AI with Machine
AI with Machine
-
Course Content 0/19
-
Lecture 1.1Introduction with Artificial Intelligence.
-
Lecture 1.2ML and other related terms to AI.
-
Lecture 1.3A working example of AI and ML.
-
Lecture 1.4These simple tasks are to make you understand how AI
-
Lecture 1.5and ML can find their applications in real life.
-
Lecture 1.6Python libraries for ML.
-
Lecture 1.7Setting up Anaconda development environment.
-
Lecture 1.8Verifying proper installation of Anaconda environment.
-
Lecture 1.9Getting into core development of ML.
-
Lecture 1.10Different ML techniques.
-
Lecture 1.11Introduction of Ai with Deep Learning
-
Lecture 1.12PyTorch Fundamentals: Matrices
-
Lecture 1.13PyTorch Fundamentals: Variables and Gradients
-
Lecture 1.14Linear Regression with PyTorch
-
Lecture 1.15Logistic Regression with PyTorch
-
Lecture 1.16Feedforward Neural Network with PyTorch
-
Lecture 1.17Convolutional Neural Network (CNN) with PyTorch
-
Lecture 1.18Recurrent Neural Networks (RNN)
-
Lecture 1.19Long Short-Term Memory Networks (LSTM)
-
This content is protected, please login and enroll course to view this content!