convolutional neural networks many resources are available for free google colab and kaggle provide excellent places to start experimenting with deep learning summary this covered the basics of cnns the key takeaways are the convolution operationthe pooling operationhow they are used in conjunctionand how features are not hand-engineered but learned cnns are the most successful application of deep learning and embody the idea of learning features/representations rather than hand-engineering them the exercises in this explored cnns using both fairly simple dataset and moderately large dataset with training from scratch we also leveraged pretrained networks and saw the performance boost achieved as result in the next we will explore recurrent neural networkswhich are widely used in the field of natural language processing and speech recognition