CNNs with TensorFlow: Basics of Machine Learning
Completed by Arjun Angirus
January 24, 2026
2 hours (approximately)
Arjun Angirus's account is verified. Coursera certifies their successful completion of CNNs with TensorFlow: Basics of Machine Learning
What you will learn
Adapt the main components of neural networks: inputs, layers, weights, and activation functions according to the specific application.
Use TensorFlow and Keras to design, implement, and adapt convolutional neural networks for image recognition tasks.
Evaluate neural network models and measure their accuracy, modify the parameters of the model if needed to improve its accuracy.
Skills you will gain
- Category: Model Training
- Category: Adaptability
- Category: Artificial Neural Networks
- Category: Image Analysis
- Category: Matplotlib
- Category: Keras (Neural Network Library)
- Category: Plot (Graphics)
- Category: Model Optimization
- Category: Deep Learning
- Category: Applied Machine Learning
- Category: Tensorflow
- Category: Python Programming
