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Building Advanced Deep Learning and NLP Projects
Gain insights into advanced deep learning and NLP by building 12 real-world projects using tools like TensorFlow and scikit-learn. Enhance your portfolio with industry-relevant skills.
4.6
57 Lessons
5h
Join 2.9 million developers at
Join 2.9 million developers at
Learning Roadmap
2.
Project: Build a COVID-19 Detection System Using X-Rays
Project: Build a COVID-19 Detection System Using X-Rays
Get started with building a COVID-19 detection system using CNNs and image data.
3.
Project: Building a Pokemon Classifier Using Transfer Learning
Project: Building a Pokemon Classifier Using Transfer Learning
11 Lessons
11 Lessons
Go hands-on with building a Pokemon classifier using transfer learning and ResNet50.
4.
Project: Text Generation Using Markov Chains
Project: Text Generation Using Markov Chains
7 Lessons
7 Lessons
Apply your skills to build a text generator using Markov chains for dynamic text creation.
5.
Word Embedding: Two Mini Projects
Word Embedding: Two Mini Projects
8 Lessons
8 Lessons
Take a closer look at word embeddings, advanced NLP techniques, and practical mini projects.
6.
Project: IMDB Reviews Sentiment Analysis
Project: IMDB Reviews Sentiment Analysis
11 Lessons
11 Lessons
Follow the process of building an RNN for IMDB sentiment analysis, covering architectures, LSTMs, embedding layers, model training, and assignments.
7.
Project: Deciphering Text Using Character-Level RNNs
Project: Deciphering Text Using Character-Level RNNs
3 Lessons
3 Lessons
Master the steps to build, train, and evaluate a character-level RNN model for text decryption.
8.
Project: Emoji Predictor Using Transfer Learning in NLP
Project: Emoji Predictor Using Transfer Learning in NLP
3 Lessons
3 Lessons
Try out building an emoji predictor using GloVe, LSTMs, and transfer learning.
10.
Where to Go Next?
Where to Go Next?
2 Lessons
2 Lessons
Break apart project ideas and next steps for advancing deep learning and NLP skills.
Certificate of Completion
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ABOUT THIS COURSE
In this course, you'll not only learn advanced deep learning concepts, but you'll also practice building some advanced deep learning and Natural Language Processing (NLP) projects. By the end, you will be able to utilize deep learning algorithms that are used at large in industry.
This is a project-based course with 12 projects in total. This will get you used to building real-world applications that are being used in a wide range of industries. You will be exposed to the most common tools used for machine learning projects including: NumPy, Matplotlib, scikit-learn, Tensorflow, and more.
It’s recommended that you have a firm grasp in these topic areas: Python basics, Numpy and Pandas, and Artificial Neural Networks.
Once you’re finished, you will have the experience to start building your own amazing projects, and some great new additions to your portfolio.
ABOUT THE AUTHOR
Harsh Jain
Software Developer @ Springworks | Ex-TCS | Mentor & Coding Instructor | NodeJS | Python | ReactJS | Author @ Educative.io
Trusted by 2.9 million developers working at companies
A
Anthony Walker
@_webarchitect_
E
Evan Dunbar
ML Engineer
S
Software Developer
Carlos Matias La Borde
S
Souvik Kundu
Front-end Developer
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Vinay Krishnaiah
Software Developer
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