Natural Language Processing (NLP) uses algorithms to understand and manipulate human language. This technology is one of the most broadly applied areas of machine learning. 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.
By 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. These and other NLP applications are going to be at the forefront of the coming transformation to an AI-powered future.
This Specialization is designed and taught by two experts in NLP, machine learning, and deep learning. Younes Bensouda Mourri is an Instructor of AI at Stanford University who also helped build the Deep Learning Specialization. Łukasz Kaiser is a Staff Research Scientist at Google Brain and the co-author of Tensorflow, the Tensor2Tensor and Trax libraries, and the Transformer paper.
WHAT YOU WILL LEARN
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 network in TensorFlow & 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
Coursera
Dive into the world of Natural Language Processing with Coursera's 'Natural Language Processing with Probabilistic Models' course. This specialized program will guide you through creating advanced algorithms for text correction, part-of-speech tagging, and more, using probabilistic models to understand and manipulate language data.
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Embark on a journey into the fascinating world of Natural Language Processing with this introductory course from Coursera's Natural Language Processing Specialization by deeplearning.ai. Gain expertise in performing sentiment analysis, understanding vector space models, reducing dimensionality with PCA, and creating basic translation algorithms using pre-computed word embeddings.
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Dive into the world of Natural Language Processing with our specialized course. Learn to train neural networks for sentiment analysis, generate synthetic text, perform named entity recognition, and compare questions using advanced sequence models such as Gated Recurrent Units (GRU) and Long Short-Term Memory (LSTM). This course is perfect for those looking to enhance their skills in NLP and apply them to real-world problems.
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Dive into the world of Natural Language Processing with our expert-led course on Attention Models. Whether you're a budding data scientist or an experienced software engineer, this course will equip you with the skills to understand and implement advanced NLP techniques using attention models. Start your journey towards mastering natural language understanding today!