![]() ![]() In Course 1: NLP with Classification and Vector Spaces,Īll the programming assignments and ungraded labs have been refactoredĪll programming assignments have new automatic graders Learn T5, BERT, transformer, reformer, and more with □ Transformers! Use encoder-decoder, causal, and self-attention to perform advanced machine translation of complete sentences, text summarization, question-answering, and to build chatbots.Use dense and recurrent neural networks, LSTMs, GRUs, and Siamese networks in TensorFlow and Trax to perform advanced sentiment analysis, text generation, named entity recognition, and to identify duplicate questions.Use dynamic programming, hidden Markov models, and word embeddings to autocorrect misspelled words, autocomplete partial sentences, and identify part-of-speech tags for words.Use logistic regression, naïve Bayes, and word vectors to implement sentiment analysis, complete analogies, translate words, and use locality-sensitive hashing to approximate nearest neighbors.This Specialization will equip you with machine learning basics and state-of-the-art deep learning techniques needed to build cutting-edge NLP systems: Łukasz Kaiser Opens in a new tab is a Staff Research Scientist at Google Brain and the co-author of Tensorflow, the Tensor2Tensor and Trax libraries, and the Transformer paper. Younes Bensouda Mourri Opens in a new tab is an Instructor of AI at Stanford University who also helped build the Deep Learning Specialization Opens in a new tab. This Specialization is designed and taught by two experts in NLP, machine learning, and deep learning. These and other NLP applications are going to be at the forefront of the coming transformation to an AI-powered future Opens in a new tab. As AI continues to expand, so will the demand for professionals skilled at building models that analyze speech and language, uncover contextual patterns, and produce insights from text and audio.īy the end of this Specialization, you will be ready to design NLP applications that perform question-answering and sentiment analysis, create tools to translate languages and summarize text, and even build chatbots. This technology is one of the most broadly applied areas of machine learning and is critical in effectively analyzing massive quantities of unstructured, text-heavy data. Its support for speech and image translations also makes it easier to translate large amounts of text.Natural Language Processing (NLP) is a subfield of linguistics, computer science, and artificial intelligence that uses algorithms to interpret and manipulate human language. ![]() ![]() With its ability to provide numerous possible translations for a single phrase or sentence, you can easily find which one best fits a given context. Great for language learnersĪlthough there’s still room for improvement when it comes to DeepL Translate’s ability to provide romanized text and underprepared servers, it’s still a phenomenal app overall. There are also instances where you can run into an error that prevents you from translating text due to a high volume of other users making use of the app’s servers at the same time. Something to note, though, is that certain languages with their own alphabets do not have romanizations, which can make it difficult to read text on your own unless you have knowledge of the aforementioned alphabet. You can even save translations to reference them at a later time. There’s even a feature to have the translated text converted to audio so it can be spoken out loud in real-time. With support for speech and image translations, you can get translations quickly without having to worry about how to type special characters or typing down something that was said to you in passing. As mentioned above, the app also provides users with other possible translations so you can get the literal meaning of something, as well. With accurate translations that capture idiosyncrasies in a language, you can easily learn how locals or native speakers would say a certain phrase or sentence. Whether you’re learning a new language or visiting a different country, having a tool like DeepL Translate can be a great help. ![]()
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