Natural Language Processing: The Beginner's Guide (Career Conversations)
🔍 Ever wondered how chatbots, voice assistants, and recommendation systems understand human language? Look no further than Natural Language Processing (NLP)—the technology that enables computers to interpret, generate, and respond to human language.
In this installment of Tech Career Conversations, Dakota Nunley chats with Dr. Uohna Thiessen, a leading data scientist and AI strategist, about the fundamentals of NLP, its real-world applications, and how to get started in this exciting field.
What You’ll Learn in This Video:
- What is Natural Language Processing (NLP) and why is it important?
- Common applications of NLP (chatbots, virtual assistants, search engines, and more)
- Why NLP is one of the most challenging fields in AI
- How deep learning has transformed NLP in recent years
- The impact of Transformer models (like BERT & GPT) on NLP
- Key NLP concepts: tokenization, sentiment analysis, text classification
- The role of data pre-processing in building NLP models
- NLP’s role in virtual assistants, chatbots, and recommendation systems
- Challenges in NLP: bias, hallucinations, and ethical concerns
- Beginner-friendly projects & resources to start learning NLP today
Whether you’re new to Natural Language Processing (NLP) or looking to expand your AI & machine learning knowledge, this discussion will give you valuable insights into how NLP models work and how to get started.
🔑 Resources & Links:
- Learn NLP & Machine Learning with Udacity: https://www.udacity.com/ai
- Kaggle NLP Datasets: https://www.kaggle.com/datasets
- Google Colab (Free Python Environment): https://colab.research.google.com
- Deep Learning AI Courses by Andrew Ng: https://www.deeplearning.ai
Enjoyed this video? 💙
- Like this video if you found it helpful
- Comment below with your thoughts & questions on NLP
- Subscribe to Udacity for more AI & Data Science content
- Turn on notifications so you don’t miss future AI discussions
---
Follow Dr. Uohna Thiessen on LinkedIn: https://www.linkedin.com/in/druohna-datascientist/
---
Connect with us on social! 🌐
Instagram: https://www.instagram.com/udacity/
LinkedIn: https://www.linkedin.com/school/udacity/
Facebook: https://www.facebook.com/Udacity/
X/Twitter: https://twitter.com/udacity
---
Video Chapters:
00:00 Introductions
02:00 - What is NLP?
03:00 - Common applications of NLP
04:00 - Why is NLP so difficult?
05:00 Foundational Skills for NLP
06:10 How has NLP evolved in recent years?
11:27 Key Concepts in NLP
15:18 The Role of Pre-Processing in NLP
19:13 What makes TikTok’s recommendation system so addictive?
21:13 Challenges and Opportunities in NLP
25:58 Getting Started with NLP
29:00 - How To Stay Up-to-date On NLP
#NaturalLanguageProcessing #NLP #AI #MachineLearning #DeepLearning #AIModels #ChatGPT #BERT #TransformerModels #PythonNLP #TextAnalysis #DataScience #Udacity #DakotaNunley #DrUohnaThiessen
🔍 Ever wondered how chatbots, voice assistants, and recommendation systems understand human language? Look no further than Natural Language Processing (NLP)—the technology that enables computers to interpret, generate, and respond to human language.
In this installment of Tech Career Conversations, Dakota Nunley chats with Dr. Uohna Thiessen, a leading data scientist and AI strategist, about the fundamentals of NLP, its real-world applications, and how to get started in this exciting field.
What You’ll Learn in This Video:
– What is Natural Language Processing (NLP) and why is it important?
– Common applications of NLP (chatbots, virtual assistants, search engines, and more)
– Why NLP is one of the most challenging fields in AI
– How deep learning has transformed NLP in recent years
– The impact of Transformer models (like BERT & GPT) on NLP
– Key NLP concepts: tokenization, sentiment analysis, text classification
– The role of data pre-processing in building NLP models
– NLP’s role in virtual assistants, chatbots, and recommendation systems
– Challenges in NLP: bias, hallucinations, and ethical concerns
– Beginner-friendly projects & resources to start learning NLP today
Whether you’re new to Natural Language Processing (NLP) or looking to expand your AI & machine learning knowledge, this discussion will give you valuable insights into how NLP models work and how to get started.
🔑 Resources & Links:
– Learn NLP & Machine Learning with Udacity: https://www.udacity.com/ai
– Kaggle NLP Datasets: https://www.kaggle.com/datasets
– Google Colab (Free Python Environment): https://colab.research.google.com
– Deep Learning AI Courses by Andrew Ng: https://www.deeplearning.ai
Enjoyed this video? 💙
– Like this video if you found it helpful
– Comment below with your thoughts & questions on NLP
– Subscribe to Udacity for more AI & Data Science content
– Turn on notifications so you don’t miss future AI discussions
—
Follow Dr. Uohna Thiessen on LinkedIn: https://www.linkedin.com/in/druohna-datascientist/
—
Connect with us on social! 🌐
Instagram: https://www.instagram.com/udacity/
LinkedIn: https://www.linkedin.com/school/udacity/
Facebook: https://www.facebook.com/Udacity/
X/Twitter: https://twitter.com/udacity
—
Video Chapters:
00:00 Introductions
02:00 – What is NLP?
03:00 – Common applications of NLP
04:00 – Why is NLP so difficult?
05:00 Foundational Skills for NLP
06:10 How has NLP evolved in recent years?
11:27 Key Concepts in NLP
15:18 The Role of Pre-Processing in NLP
19:13 What makes TikTok’s recommendation system so addictive?
21:13 Challenges and Opportunities in NLP
25:58 Getting Started with NLP
29:00 – How To Stay Up-to-date On NLP
#NaturalLanguageProcessing #NLP #AI #MachineLearning #DeepLearning #AIModels #ChatGPT #BERT #TransformerModels #PythonNLP #TextAnalysis #DataScience #Udacity #DakotaNunley #DrUohnaThiessen
