Completed following tasks:

1. Download Data File from https://archive.ics.uci.edu/ml/datasets/Character+Trajectories
2. Write a Python script to read and plot the data
3. Visualize one character of each class using your script.
4. Write a Python script to train and test a 1D-CNN classifier:
5. Execute your script and evaluate the performance of the classifier.
6. Write a script to visualize the activations of one layer.

To complete the task I have used differnt materials available online, some of them I have listed below:

1. https://towardsdatascience.com/visualizing-intermediate-activation-in-convolutional-neural-networks-with-keras-260b36d60d0
2. https://jjallaire.github.io/deep-learning-with-r-notebooks/notebooks/5.4-visualizing-what-convnets-learn.nb.html
3. https://github.com/ShuningZhao/Character-Trajectories/tree/0c9bfa477542c4f885370a6af05a99b45764f3af
4. https://missinglink.ai/guides/keras/keras-conv1d-working-1d-convolutional-neural-networks-keras/
5. https://machinelearningmastery.com/cnn-models-for-human-activity-recognition-time-series-classification/
6. https://modelzoo.co/model/tdd