How to build a project in SmartInternz/step by step guide in telugu

Описание: contact me in Linkedin: www.linkedin.com/in/edara-manikanta

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Deep Learning code:

from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Conv2D, MaxPooling2D, Flatten, Dense, Dropout, Input
from tensorflow.keras.preprocessing.image import ImageDataGenerator
from tensorflow.keras.optimizers import Adam

IMAGE_SIZE = (224, 224)
BATCH_SIZE = 32
EPOCHS = 10

TRAIN_DIR = "paste your url"
VALID_DIR = "paste your url"

Data Generators
train_gen = ImageDataGenerator(rescale=1./255)
val_gen = ImageDataGenerator(rescale=1./255)

train_data = train_gen.flow_from_directory(
TRAIN_DIR,
target_size=IMAGE_SIZE,
batch_size=BATCH_SIZE,
class_mode='categorical'
)

val_data = val_gen.flow_from_directory(
VALID_DIR,
target_size=IMAGE_SIZE,
batch_size=BATCH_SIZE,
class_mode='categorical'
)

Number of classes
num_classes = len(train_data.class_indices)

Model
model = Sequential([
Input(shape=(224, 224, 3)),
Conv2D(32, (3, 3), activation='relu'),
MaxPooling2D(2, 2),
Conv2D(64, (3, 3), activation='relu'),
MaxPooling2D(2, 2),
Flatten(),
Dense(128, activation='relu'),
Dropout(0.5),
Dense(num_classes, activation='softmax')
])

model.compile(optimizer=Adam(), loss='categorical_crossentropy', metrics=['accuracy'])

Train the model
model.fit(train_data, validation_data=val_data, epochs=EPOCHS)

Save as .h5
model.save("your_model_name.h5")
print("✅ your_model_name.h5 saved!")