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NLP: Natural Language Processing (Text)

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    3. NLP: Natural Language Processing (Text)
    4. NLP Topics Overview Videos
    5. Part - 8: NLP and Text Classification: পর্ব - 8: N...
    Cliquer le lien https://youtu.be/kgYHJkmnIfI?list=PLUA7SYgJYDFq0wxkY0z6q7A2csO0W3mjf pour ouvrir la ressource.
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        • NLP: Natural Language Processing (Text)

          • Généralités

          • Faculty/Teacher/Instructor/Professor

          • NLP Topics Overview Videos

            • URLPart - 1: NLP: High Level Overview of the Course

            • URLPart-2: Introductory terms for NLP. Applications o...

            • URLPart - 3:NLP:Programming Languages & Tools. পা...

            • URLhttps://youtu.be/XT0nglEqquI?list=PLUA7SYgJYDFq0wx...

            • URLPart - 5 : Language Modeling for Natural Language ...

            • URLAnnotation icon WebAdvisor logo NLP - Natural Lan...

            • URLPart - 7 : NLP Overview: POS Tagging

            • URLPart - 8: NLP and Text Classification: পর্ব - 8: N...

            • URLPart - 9: Neural Language Models: পার্ট - 9: নিউরা...

            • URLPart - 10 : Word Embeddings for Natural Language P...

            • URL(Needs Re-recording) Part - 11: RNN for NLP applic...

            • URLPart - 12: Text Clustering. Natural Language Proce...

            • URLPart - 13: Topic Modeling. Natural Language Proces...

          • Detail Discussion of the Topics

          • Potential NLP problems (assignments) to solve

          • Programming CODE Demo

          • Industry Project Ideas

          • Research Project Ideas

          • Tools and Software

          • Assignments

          • Project

          • Section 11

          • Section 12

          • Section 13

          • Section 14

          • Section 15

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    This course will discuss, explain NLP technologies. You will be able to utilize those concepts and technologies to create NLP applications even for Real Life. You will also achieve Hands-on Skills to write NLP applications. Hands-on skills will be shown using tools such as Python (Primary), R, NLTK, Keras/Tensorflow and misc.

    Initially, we will check all topics conceptually.

    Then we will implement (show) the core concepts. And will see how  those are utilized in real applications. Afterward, we will dig into Mathematical Stuff. On an ongoing basis in the concept overview and/or implementation we will also show the analysis, application, and critical thinking approach with those concepts and implementations. 

    Real Life Projects and Assignments

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