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Machine Learning on Google Cloud: Sequence and Text Models
Highest Rated
Rating: 4.6 out of 5(51 ratings)
400 students

Machine Learning on Google Cloud: Sequence and Text Models

Advanced Machine Learning on Google Cloud: Sequence Models & NLP (Natural Language Processing) on Google Cloud
Created byMinerva Singh
Last updated 10/2023
English

What you'll learn

  • Introduction to getting started with Google Cloud Platform (GCP)
  • Reading in and processing text data within GCP
  • Implement common natural language processing (NLP) techniques such as entity analysis and keyword detection on text data
  • Carry out text classification using deep leaning models
  • Getting started with OpenAI for Large Language Model (LLM) based text analysis

Course content

8 sections47 lectures3h 28m total length
  • Welcome To the Course2:25

    Explore Google Cloud sequence and text models for language processing, NLP and LLM workflows, including chatbots, speech to text, and subtitles, with NLTK, Gensim, OpenAI, and Hugging Face.

  • Data and Code0:07
  • Python Installation5:44
  • Installing Packages In Google Colab4:27

    Discover how Google Colab ships with pre-installed deep learning packages like Keras and TensorFlow, plus text processing tools, and learn to install additional packages with !pip.

Requirements

  • Should have prior experience of Python data science
  • Prior experience of statistical and machine learning techniques will be beneficial
  • Should have an interest in extracting insights from text analysis
  • Should have an interest in applying machine learning models on text data

Description

Natural language processing (NLP) is a subfield of artificial intelligence (AI) that enables computers to comprehend spoken and written human language. NLP has several applications, including text-to-voice and speech-to-text conversion, chatbots, automatic question-and-answer systems (Q&A), automatic image description creation, and video subtitles. With the introduction of ChatGPT, both NLP and Large Language Models (LLMs) will become increasingly popular, potentially leading to increased employment opportunities in this branch of AI. Google Cloud Processing (GCP) offers the potential to harness the power of cloud computing for larger text corpora and develop scalable text analysis models.

My course provides a foundation for conducting PRACTICAL, real-life NLP and LLM-based text analysis using GCP. By taking this course, you are taking a significant step forward in your data science journey to become an expert in harnessing the power of text data for deriving insights and identifying trends.

Why Should You Take My Course?

I have an MPhil (Geography and Environment) from the University of Oxford, UK. I also completed a data science PhD (Tropical Ecology and Conservation) at Cambridge University.

I have several years of experience analyzing real-life data from different sources and producing publications for international peer-reviewed journals.

This course will help you gain fluency in GCP text analysis using NLP techniques, OpenAI, and LLM analysis. Specifically, you will

  • Gain proficiency in setting up and using Google Cloud Processing (GCP) for Python Data Science tasks

  • Carry out standard text extraction techniques.

  • Process the extracted textual information in a usable form via preprocessing techniques implemented via powerful Python packages such as NTLK.

  • A thorough grounding in text analysis and NLP-related Python packages such as NTLK, Gensim among others

  • Use deep learning models to perform everyday text analytics tasks such as text classification.

  • Introduction to common LLM frameworks such as OpenAI and Hugging Face.

In addition to all the above, you’ll have MY CONTINUOUS SUPPORT to ensure you get the most value from your investment!

ENROLL NOW :)

Who this course is for:

  • People who wish to learn practical text mining and natural language processing
  • People who wish to derive insights from textual data
  • People wanting to harness the power of cloud computing via GCP