Deep Learning

Desciptions only:  1.       Image Classification For Image classification binary, CNN will have one nueron at output layer. In this experiment  of Image classification,  sample images of dogs are trained , tested and prediction using a basic CNN Network. 2.      Actor Age groups For Image classification and labeling the images into Young, Middle, and Old in this experiment, A CNN of three layers used and by inputting training data with labeling. 3. Hyper parameted tuning Hyper parameters are the parameters given in the program. Tuning involves modifying parameters to try perforamce 4. Sequential data prediction Training Sequential data prediction models from various days . 5. Image denoising Training Image noinse models to denoise roman numbers  6. YOLO      YOLO prgromas are used to detect objects.  7. Binary logistic loss Optimization purpose 8.  Alexnet  CIFAR Dataset and Classifcation of CIFAR -10, ...

Fill out this Google form by selecting Project Number from List of Projects:  https://forms.gle/noVGBGDRc55yyY8y7 List of Projects: 11. List of Capstone Projects for SOC - Deep Learning (dlpatterns.blogspot.com)

  1. What will be the output of the following code? x = [ 1 , 2 , 3 ] y = x y.append( 4 ) print (x) A) [1, 2, 3] B) [1, 2, 3, 4] ✅ C) [4] D) Error Explanation: Lists are mutable, and y references the same object as x . So changes in y affect x . 2. Which of the following is not a valid keyword in Python? A) pass B) assert C) eval D) then ✅ Explanation: then is not a Python keyword. 3. What is the output? print ( bool ( 0 ), bool ( 3.5 ), bool (- 1 )) A) False True True ✅ B) False False False C) True True True D) Error Explanation: In Python, 0 is False. Any non-zero value (positive or negative) is True. 4. Which of these data types is immutable? A) list B) dict C) tuple ✅ D) set Explanation: Tuples are immutable. Lists, dicts, and sets are mutable. 5. What will the following code output? def f ( a, b= 2 , c= 3 ): return a + b + c print (f( 1 , c= 5 )) A) 6 B) 8 ✅ C) 10 D) Error Explanation: a=1, b=2 (default), c=5 (overridden) → ...

House Price Prediction   from tensorflow.keras.datasets import boston_housing from tensorflow.keras.models import Sequential from tensorflow.keras.layers import Dense # Load dataset (x_train, y_train), (x_test, y_test) = boston_housing.load_data() # Normalize data mean, std = x_train.mean(axis= 0 ), x_train.std(axis= 0 ) x_train = (x_train - mean) / std x_test = (x_test - mean) / std # Define model model = Sequential([     Dense( 64 , activation= 'relu' , input_shape=(x_train.shape[ 1 ],)),     Dense( 64 , activation= 'relu' ),     Dense( 1 ) ]) # Compile model model. compile (optimizer= 'adam' , loss= 'mse' , metrics=[ 'mae' ]) # Train model model.fit(x_train, y_train, epochs= 50 , batch_size= 8 , validation_data=(x_test, y_test)) # -------- Prediction Step -------- # Predict on test set predictions = model.predict(x_test) # Display first 5 predictions with actual values for i in range ( 5 ):     print ( f "Predicted Price: {predict...

 https://drive.google.com/file/d/1l93Bv7MheGBbol6UmzsOz-2Du8OLj5mh/view?usp=sharing

  AIM :   Design Artificial Neural Networks for Identifying and Classifying an actor using Kaggle Dataset. Link to download Model file: https://drive.google.com/file/d/12lsyOHe5QifEaiW_d9K8BLLy5PeCEWsf/view?usp=sharing Link to Images to test: https://drive.google.com/drive/folders/1xhQJSzL_OL72YXBgdQD10_JmYpHPngLu?usp=sharing Program to predict Face Image's Age group: from tensorflow.keras.models import load_model from PIL import Image import numpy as np # Define the input image dimensions image_height = 128 image_width = 128 num_channels = 3 # Load the trained model model = load_model( '/content/drive/MyDrive/trained_model_C_Dataset.h5' ) # Replace 'your_trained_model.h5' with the actual file name # Read the new face image new_face_path = '/content/drive/MyDrive/2_Predict/old.jpeg'   # Replace 'path_to_new_face.jpg' with the actual file path new_face = Image. open (new_face_path) display(new_face) # Preprocess the image new_face = new_face.re...