| Day 5.2 LSTM (Long Short-Term Memory) network using TensorFlow and Keras.ipynb | 19.7 KB | |
| Day1 Probability Distribution Using NumPy .ipynb | 39.1 KB | |
| LSTM (Long Short-Term Memory) network using TensorFlow and Keras.ipynb | 14.1 KB | |
| DAY 7 GAN Lab -3.ipynb | 720.9 KB | |
| Day 2 Understanding Neural Network.ipynb | 2.6 MB | |
| Day 2 Case Study Exploratory Data Analysis.ipynb | 5.5 MB | |
| Day 2 RNN Fundamentals for Gen AI.ipynb | 53.8 KB | |
| Day 2 Synthetic Data Generation using Python.ipynb | 121.6 KB | |
| Day 3 Running SQL Queries .ipynb | 12.2 KB | |
| Day 4 Understanding Recurrent Neural Networks (RNNs) and its example in Sequence Generation.ipynb | 1.3 MB | |
| Day 4.4 RNN for Sequence Generation .ipynb | 18.4 KB | |
| Day 5.1 RNN for Text Sequence.ipynb | 39 KB | |
| Day 5.2 LSTM in Sequence Generation.ipynb | 244.3 KB | |
| Day 6 Basic Generative Adversarial Network (GAN) implemented using Python. .ipynb | 345.2 KB | |
| Day 6 Convolutional Neural Networks (CNNs).ipynb | 190 KB | |
| Day 6 GAN Fundamentals and Unsupervised Training.ipynb | 1.5 MB | |
| Day 6 GANS_lab1.ipynb | 36.3 KB | |
| Day 7 Transformers.ipynb | 496.3 KB | |
| Day1 Data Visualization using Matplotlib.ipynb | 204 KB | |
| Day1 Visualization using Seaborne.ipynb | 358.6 KB | |
| Day1 part 2 Data Manipulation using Pandas.ipynb | 40.1 KB | |
| Examples Hypothesis Testing .ipynb | 11.1 KB | |
| Lab 1 Data Manipulation and Visualization using Python.ipynb | 2.6 KB | |
| Lab 2 Implement RNN.ipynb | 22.6 KB | |
| Lab 3 RNN implementation.ipynb | 10.5 KB | |
| demo | 1 bytes | |
