CNN-in-Tensorflow

• This series of notebooks demonstrates techniques to build and optimize ConvNet models for various image classification tasks, ensuring robust and generalizable performance

• Particularly demonstrates Data preprocessing, model building, augmentation techniques, transfer learning, and multiclass classification

• Kaggle Dataset - https://www.kaggle.com/c/dogs-vs-cats/overview

• These notebooks are submitted as part of assignments while completing a course in Coursera https://www.coursera.org/learn/convolutional-neural-networks-tensorflow

• Skills -> ConvNets, Overfitting, Data Augumentation, Keras ImageDataGenerator, Dropout, Multi-class classifier, Tensorflow, Python

• Included Notebooks

  • Cats_vs_Dogs_Image_Classifier
    • https://github.com/TechWithRamaa/ConvNets-in-Tensorflow/blob/main/Cats_vs_Dogs_Image_Classifier.ipynb
  • Tackling_Overfitting_Cats_vs_Dogs_Classifier
    • https://github.com/TechWithRamaa/ConvNets-in-Tensorflow/blob/main/Tackling_Overfitting_Cats_vs_Dogs_Classifier.ipynb
  • Pre_Trained_Model_For_Cats_vs_Dog_Classifier
    • https://github.com/TechWithRamaa/ConvNets-in-Tensorflow/blob/main/Pre_Trained_Model_For_Cats_vs_Dog_Classifier.ipynb
  • Multi_Class_Classifier_Sign_Language
    • https://github.com/TechWithRamaa/ConvNets-in-Tensorflow/blob/main/Multi_Class_Classifier_Sign_Language.ipynb