DL--Models-

Welcome to the DL-Models repository! This repository contains a collection of deep learning models implemented using popular frameworks such as TensorFlow and PyTorch. Each model is organized in a structured manner with training, evaluation, and usage instructions.

Here’s a list of 100 deep learning models, ranging from basic to advanced:

1. Logistic Regression
2. Linear Regression
3. Perceptron
4. Multi-Layer Perceptron (MLP)
5. Simple Neural Network
6. Single Layer Feedforward Neural Network
7. Autoencoder
8. Sparse Autoencoder
9. Denoising Autoencoder
10. Convolutional Neural Network (CNN)
11. Basic RNN
12. Gated Recurrent Unit (GRU)
13. Long Short-Term Memory (LSTM)
14. Word2Vec
15. FastText
16. Skip-Gram Model
17. Continuous Bag of Words (CBOW)
18. Fully Connected Neural Network (FCNN)

Intermediate Models

21. LeNet-5
22. VGG-16
23. VGG-19
24. Inception-v1 (GoogLeNet)
25. Inception-v3
26. ResNet-50
27. ResNet-101
28. ResNet-152
29. DenseNet
30. MobileNet
31. MobileNetV2
32. Xception
33. U-Net
34. FCN-8
35. RCNN (Region-based CNN)
36. Fast RCNN
37. Faster RCNN
38. YOLO (You Only Look Once)
39. YOLOv3
40. SSD (Single Shot Multibox Detector)
41. SqueezeNet
42. ShuffleNet
43. NASNet
44. Transformer
45. BERT (Bidirectional Encoder Representations from Transformers)
46. GPT (Generative Pretrained Transformer)
47. GPT-2
48. GPT-3
49. BERT-Base
50. BERT-Large

Advanced Models

51. CycleGAN
52. Pix2Pix
53. DeepLab
54. SegNet
55. Mask RCNN
56. EfficientNet
57. Vision Transformer (ViT)
58. Swin Transformer
59. Neural Style Transfer
60. BigGAN
61. StyleGAN
62. StyleGAN2
63. Neural Turing Machines (NTM)
64. Differentiable Neural Computers (DNC)
65. WaveNet
66. Tacotron
67. Tacotron 2
68. Deep Speech
69. AlphaGo
70. AlphaZero
71. Reinforcement Learning with Q-Learning
72. Deep Q-Network (DQN)
73. Double DQN
74. Dueling DQN
75. Proximal Policy Optimization (PPO)
76. A3C (Asynchronous Advantage Actor-Critic)
77. Soft Actor-Critic (SAC)
78. Variational Autoencoder (VAE)
79. Beta-VAE
80. DCGAN (Deep Convolutional GAN)
81. Wasserstein GAN (WGAN)
82. WGAN-GP
83. Progressive GAN
84. Attention GAN
85. BigGAN
86. OpenAI CLIP
87. BART (Bidirectional and Auto-Regressive Transformers)
88. T5 (Text-To-Text Transfer Transformer)
89. DeeplabV3+
90. ConvLSTM
91. Reformer
92. Detr (DEtection TRansformers)
93. FastSpeech
94. FastSpeech 2
95. S3 (State Space Model)
96. T5 (Text-To-Text Transfer Transformer)
97. AdaIN (Adaptive Instance Normalization)
98. Taming Transformers
99. Implicit Neural Representations
100. NeRF (Neural Radiance Fields)