- RNNs
- Computer Vision
- Convolutional Neural Network
- Forecasting
- Transfer Learning
- Time Series
- Machine Learning
- Tokenization
- Dropouts
- Natural Language Processing
- TensorFlow
- Augmentation
August 2, 2019
Approximately 2 months at 10 hours a week to completeNuno Ramos Carvalho's account is verified. Coursera certifies their successful completion of DeepLearning.AI DeepLearning.AI TensorFlow Developer Specialization.
Course Certificates Completed
Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
Convolutional Neural Networks in TensorFlow
Natural Language Processing in TensorFlow
Sequences, Time Series and Prediction
Best practices for TensorFlow, a popular open-source machine learning framework to train a neural network for computer vision applications.
Handle real-world image data and explore strategies to prevent overfitting, including augmentation and dropout.
Build natural language processing systems using TensorFlow.
Apply RNNs, GRUs, and LSTMs as you train them using text repositories.
Earned after completing each course in the Specialization
DeepLearning.AI
Taught by: Laurence Moroney
Completed by: Nuno Ramos Carvalho by May 5, 2019
4 weeks, 4-5 hours/week
DeepLearning.AI
Taught by: Laurence Moroney
Completed by: Nuno Ramos Carvalho by May 6, 2019
4 weeks of study, 4-5 hours/week
DeepLearning.AI
Taught by: Laurence Moroney
Completed by: Nuno Ramos Carvalho by July 10, 2019
4 weeks of study, 4-5 hours/week
DeepLearning.AI
Taught by: Laurence Moroney
Completed by: Nuno Ramos Carvalho by August 2, 2019
4 weeks of study, 4-5 hours/week