2 Months | 8 WEEKS | 4 hours per week (OR) 1 Month | 4 Weeks | 8 hours per week | FILLING FAST
1 Course | 16 Modules | 32 hrs | online
Course Price | Students : Rs. 10000 | Working Professionals : Rs. 20000
2 Months | 8 Weeks | 4 hours per week (OR) 1 Month | 4 Weeks | 8 hours per week | FILLING FAST
1 Course | 16 Modules | 32 hrs | online
Course Price | Students : Rs. 10000 | Working Professionals : Rs. 20000
10 Modules | 20 hrs | online
Course Details
ENROLL NOW
10 Modules | 20 hrs | online
Course Details
ENROLL NOW
This course has been designed and prepared for professionals aspiring to learn Python programming and develop applications involving Neural Networks techniques such as Multilayer Back Propagation Neural Network, Self Organizing Map, Learning Vector Quantization and classification. You will also learn to solve data-driven problems and implement your solutions using the powerful Python packages. After completing this course, you will gain a broad spectrum of the Neural Networks environment and the best practices for Neural Networks techniques.
This course has been designed and prepared for professionals aspiring to learn Tensorflow programming and develop applications involving Concurrent Neural Networks for Vision techniques such as AlexNet, GoogleNet, ResNet, VGGNet and RNN Techniques. You will also learn to solve Vision-driven problems and implement your solutions using the powerful Tensorflow packages. After completing this course, you will gain a broad spectrum of CNN & RNN deep learning environment and the best practices for CNN & RNN deep learning techniques.
This course has been designed and prepared for professionals aspiring to learn Python programming and develop applications involving Reinforcement Learning techniques such as Markov models, Q-Learning and Adaptive Dynamic Programming. You will also learn to solve data-driven problems and implement your solutions using the powerful Python packages. After completing this course, you will gain a broad spectrum of the Reinforcement Learning environment and the best practices for Reinforcement Learning techniques.
This course has been designed and prepared for professionals aspiring to learn Tensorflow programming and develop applications involving Concurrent Neural Networks for Vision techniques such as AlexNet, GoogleNet, ResNet and VGGNet. You will also learn to solve Vision-driven problems and implement your solutions using the powerful Tensorflow packages. After completing this course, you will gain a broad spectrum of CNN deep learning environment and the best practices for CNN deep learning techniques.
This course has been designed and prepared for professionals aspiring to learn PyTorch programming and develop applications involving Recurrent Neural Networks techniques such as LSTM, GRU, Auto Encoder and Transfer Learning. You will also learn to solve text-driven problems and implement your solutions using the powerful PyTorch packages. After completing this course, you will gain a broad spectrum of the RNN environment and the best practices for RNN techniques.