Sentiment Analysis through Deep Learning with Keras & Python

Learn to apply sentiment analysis to your problems through a practical, real world use case.
3.95 (37 reviews)
Udemy
platform
English
language
Other
category
Sentiment Analysis through Deep Learning with Keras & Python
180
students
3 hours
content
Mar 2022
last update
$19.99
regular price

Why take this course?

🚀 Course Title: Sentiment Analysis through Deep Learning with Keras & Python

🎉 Headline: Master Sentiment Analysis and Unlock Customer Insights with Ease! 💬


Course Description:

Are you ready to transform the way you understand customer sentiment? If you're working in any domain of business, mastering sentiment analysis is a game-changer. This course is your key to unlocking valuable insights into what customers truly think about your products and services. 🎯

Why You Should Take This Course:

  • Industry Relevance: Sentiment analysis is critical in today's data-driven world, and mastery of this skill makes you indispensable.
  • Simplicity & Efficiency: We kick off with a concise, yet powerful, sentiment analysis engine written in Python—a mere 60 lines of code capable of performing at an industrial level.
  • Market Readiness: Integrating your sentiment analysis system into existing business pipelines is a breeze when using Python. This ensures a smooth transition of your new skills to the marketplace.
  • Deep Learning Mastery: Leverage deep learning models to automate and scale your sentiment analysis efforts, minimizing manual intervention and maximizing efficiency.

Course Highlights:

  • Hands-On Approach: Learn to write industry-grade sentiment analysis engines with minimal effort, thanks to our streamlined code examples.
  • Machine Learning Basics: We cover the essentials of machine learning with an emphasis on practical application—no heavy math required!
  • Real World Application: Gain a comprehensive understanding of how sentiment analysis is applied in real-world scenarios, beyond academic theory.
  • Avoiding Pitfalls: Learn best practices and tips to navigate common challenges faced by newcomers to the field.

Instructor's Profile:

  • Expertise: As a seasoned educator and researcher with a PhD in Security and a PostDoc from Max Planck Institute for Software Systems, Germany, Dr. Mohammad Naumanc brings years of expertise to the table.
  • Deep Learning Experience: With over 5 years of deep learning under his belt, Dr. Naumanc has been at the forefront of this technology, experimenting with state-of-the-art tools since their inception.
  • Proven Track Record: A best-selling instructor on Udemy with numerous highly-rated courses, Dr. Naumanc is well-versed in creating engaging and informative learning experiences.

Target Audience:

This course is designed for:

  • Professionals seeking to implement sentiment analysis in their field.
  • Those interested in leveraging deep learning for enhanced sentiment analysis.
  • Companies aiming to gauge customer satisfaction and engagement with their products or services.

Prerequisites:

  • Basic knowledge of Python (installation, variables, conditionals, loops).
  • No prior machine learning experience is required; the course will cover all necessary theory in a simple, accessible manner.

Join us to harness the power of sentiment analysis and deep learning with Keras & Python, and make data-driven decisions like never before! 🧠💫

Course Gallery

Sentiment Analysis through Deep Learning with Keras & Python – Screenshot 1
Screenshot 1Sentiment Analysis through Deep Learning with Keras & Python
Sentiment Analysis through Deep Learning with Keras & Python – Screenshot 2
Screenshot 2Sentiment Analysis through Deep Learning with Keras & Python
Sentiment Analysis through Deep Learning with Keras & Python – Screenshot 3
Screenshot 3Sentiment Analysis through Deep Learning with Keras & Python
Sentiment Analysis through Deep Learning with Keras & Python – Screenshot 4
Screenshot 4Sentiment Analysis through Deep Learning with Keras & Python

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2508484
udemy ID
14/08/2019
course created date
21/08/2019
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