- Machine Translation
- Transformers
- Sentiment Analysis
- Word2vec
- Attention Models
December 16, 2021
Approximately 3 months at 10 hours a week to completeSandesh Athawale'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 in Trax for sentiment analysis, text generation & named entity recognition.
Use encoder-decoder, causal, & self-attention to machine translate complete sentences, summarize text, build chatbots & question-answering.
Earned after completing each course in the Specialization
DeepLearning.AI
Taught by: Younes Bensouda Mourri, Łukasz Kaiser & Eddy Shyu
Completed by: Sandesh Athawale by July 15, 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: Sandesh Athawale by September 28, 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: Sandesh Athawale by October 8, 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: Sandesh Athawale by December 16, 2021
At the rate of 5 hours a week, it typically takes 4 weeks to complete one Course.