roadmap complete deep learning generative ai bangla tutorial

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creating a comprehensive tutorial on deep learning and generative ai in bangla involves several steps, including an introduction to the concepts, explanations of key techniques, and practical code examples. below is a structured roadmap and tutorial to help you understand and implement deep learning generative ai concepts. while i can’t provide the tutorial in bangla directly, i will outline it in english and you can translate it as needed.

roadmap for deep learning generative ai tutorial

1. introduction to deep learning
*what is deep learning?*
definition and importance in ai.
comparison with traditional machine learning.

*key concepts*
neural networks, layers, activation functions, loss functions
overview of different types of neural networks (cnns, rnns, etc.)

2. introduction to generative ai
*what is generative ai?*
definition and applications (image generation, text generation, etc.)

*types of generative models*
gans (generative adversarial networks)
vaes (variational autoencoders)
transformers for text generation

3. setting up the environment
*tools and libraries*
python, tensorflow, pytorch, keras
jupyter notebook for coding.

*installation*
install python and required libraries using pip:
```bash
pip install tensorflow keras torch torchvision
```

4. generative adversarial networks (gans)
*understanding gans*
architecture: generator and discriminator
the training process: adversarial training

*code example: basic gan implementation in python*
```python
import numpy as np
import matplotlib.pyplot as plt
from keras.models import sequential
from keras.layers import dense, leakyrelu
from keras.optimizers import adam

generator model
def build_generator():
model = sequential()
model.add(dense(128, input_dim=100))
model.add(leakyrelu(alpha=0.2))
model.add(dense(256))
model.add(leakyrelu(alpha=0.2))
model ...

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