Deep Learning for NLP: Introduction
Natural Language Processing
| Intermediate
- 14 Videos | 1h 17m 30s
- Includes Assessment
- Earns a Badge
In recent times, natural language processing (NLP) has seen many advancements, most of which are in deep learning models. NLP as a problem is very complicated, and deep learning models can handle that scale and complication with many different variations of neural network architecture. Deep learning also has a broad spectrum of frameworks that supports NLP problem solving out-of-the-box. Explore the basics of deep learning and different architectures for NLP-specific problems. Examine other use cases for deep learning NLP across industries. Learn about various tools and frameworks used such as - Spacy, TensorFlow, PyTorch, OpenNMT, etc. Investigate sentiment analysis and explore how to solve a problem using various deep learning steps and frameworks. Upon completing this course, you will be able to use the essential fundamentals of deep learning for NLP and outline its various industry use cases, frameworks, and fundamental sentiment analysis problems.
WHAT YOU WILL LEARN
-
discover the key concepts covered in this courserecall basic concepts of natural language processing (NLP) with deep learning (DL)illustrate various use cases in NLP across different industriesoutline the basic concepts of spaCy and TensorFlowoutline the basic concepts of Keras and PyTorchoutline the basic concepts of Open Neural Machine Translation (OpenNMT) and DeepNLdefine basic concepts of sentiment data
-
explore the end-to-end components for a natural language processing (NLP) sentiment datasetillustrate the basics of data loading and columnsdemonstrate exploratory data analysis (EDA) of sentiment datademonstrate pre-processing and feature engineering of sentiment datademonstrate simple machine learning (ML) modeling, tuning, and evaluation using Kerasdemonstrate creating accuracy graphs and graphs for loss over timesummarize the key concepts covered in this course
IN THIS COURSE
-
1.Course Overview1m 21sUP NEXT
-
2.NLP with Deep Learning4m 26s
-
3.NLP Use Cases in Deep Learning5m 13s
-
4.Basic Deep Learning Frameworks1m 40s
-
5.Intermediate Deep Learning Frameworks2m 23s
-
6.Advanced Deep Learning Frameworks2m 2s
-
7.Introduction to Sentiment Data3m 41s
-
8.Using Deep Learning Pipelines for Sentiment Data6m 15s
-
9.Sentiment Analysis - Overview & Data6m 32s
-
10.Sentiment Analysis - EDA14m 46s
-
11.Sentiment Analysis - Pre-processing6m 52s
-
12.Sentiment Analysis - Modeling & Evaluation12m 49s
-
13.Sentiment Analysis - Creating Accuracy & Loss Graphs8m 26s
-
14.Course Summary1m 5s
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
Skillsoft is providing you the opportunity to earn a digital badge upon successful completion of this course, which can be shared on any social network or business platform
Digital badges are yours to keep, forever.