- Machine Translation
- Transformers
- Sentiment Analysis
- Word2vec
- Attention Models
May 25, 2021
Approximately 3 months at 10 hours a week to completeRolando Treviño Lozano's account is verified. Coursera certifies their successful completion of DeepLearning.AI Natural Language Processing Specialization.
Course Certificates Completed
Natural Language Processing with Classification and Vector Spaces
Natural Language Processing with Probabilistic Models
Natural Language Processing with Sequence Models
Natural Language Processing with Attention Models
Use logistic regression, naïve Bayes, and word vectors to implement sentiment analysis, complete analogies & translate words.
Use dynamic programming, hidden Markov models, and word embeddings to implement autocorrect, autocomplete & identify part-of-speech tags for words.
Use recurrent neural networks, LSTMs, GRUs & Siamese networks for sentiment analysis, text generation & named entity recognition.
Use encoder-decoder, causal, & self-attention to machine translate complete sentences, summarize text, and answer questions.
Earned after completing each course in the Specialization
DeepLearning.AI
Taught by: Younes Bensouda Mourri, Łukasz Kaiser & Eddy Shyu
Completed by: Rolando Treviño Lozano by July 19, 2020
At the rate of 5 hours a week, it typically takes 4 weeks to complete one Course.
DeepLearning.AI
Taught by: Younes Bensouda Mourri, Łukasz Kaiser & Eddy Shyu
Completed by: Rolando Treviño Lozano by January 13, 2021
At the rate of 5 hours a week, it typically takes 4 weeks to complete one Course.
DeepLearning.AI
Taught by: Younes Bensouda Mourri, Łukasz Kaiser & Eddy Shyu
Completed by: Rolando Treviño Lozano by February 23, 2021
At the rate of 5 hours a week, it typically takes 4 weeks to complete one Course.
DeepLearning.AI
Taught by: Younes Bensouda Mourri, Łukasz Kaiser & Eddy Shyu
Completed by: Rolando Treviño Lozano by May 25, 2021
At the rate of 5 hours a week, it typically takes 4 weeks to complete one Course.