- Deep Learning
- Applied Machine Learning
- Image Analysis
- Matplotlib
- Model Evaluation
- Python Programming
- Problem Solving
- Artificial Neural Networks
- Keras (Neural Network Library)
- Convolutional Neural Networks
- Tensorflow
- Adaptability
CNNs with TensorFlow: Basics of Machine Learning
Completed by Muhammad Yasir Shabir
October 20, 2023
2 hours (approximately)
Muhammad Yasir Shabir'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
