Course Curriculum
| Session 0 : Course Material | |||
| Deep Learning – Course Material | 00:00:00 | ||
| Session 1 : Introduction to TensorFlow & Keras | |||
| DL.-1 Tensor Flow | 00:28:00 | ||
| DL-2 Keras | 00:34:00 | ||
| Session 2 : Fundamentals of Neural Networks | |||
| DL-3 ANN Hyper parameters Regularization | 00:22:00 | ||
| DL-4 Regularization in TensorFlow | 00:38:00 | ||
| DL-5 Activation Functions in Neural Networks | 00:27:00 | ||
| DL-6 Importance of Learning Rate | 00:28:00 | ||
| DL-7 Gradient Descent & Loss Functions | 00:26:00 | ||
| Session 3 : Convolutional Neural Networks (CNN) | |||
| DL-8 Convolutional Neural Networks (CNN) | 00:43:00 | ||
| DL-9 Image Processing with CNN | 00:27:00 | ||
| DL-10 CNN Architecture | 00:36:00 | ||
| DL-11 CNN Models and Object Detection | 00:21:00 | ||
| Session 4 : Recurrent Neural Networks (RNN) & LSTMs | |||
| DL-12 Recurrent Neural Networks (RNN) & LSTMs | 00:32:00 | ||
| DL-13 Model Building for Word Prediction | 00:21:00 | ||
| DL-14 Understanding RNN – Sequence Prediction | 00:26:00 | ||
| DL-15 Fundamentals of Long Short-Term Memory | 00:29:00 | ||
| Session 5 : Word Embeddings & Text Vectorization | |||
| DL-16 Word Embedding Text into Vectors | 00:17:00 | ||
| DL-17 Word-to-Vector, and Contextual Word | 00:16:00 | ||
| DL-18 Converting Text to Vectors and Word2Vec | 00:24:00 | ||
1000 STUDENTS ENROLLED
