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Data Science I: NDSC Edition

This course is a specialised version of our Data Science I (Python), designed specifically for the National Data Science Challenge organised by Shopee.

0

Created By : Marco A. Gutiérrez

Part Time

4 weeks

3.5 h/session

Data Science I: NDSC Edition

0 Part Time 4 weeks 3.5 h/session

What You'll Learn

- Deep learning (DL) models
- DL optimisation techniques
- The overfitting problem and how to solve it
- Structure of Convolutional Neural Networks (CNN)
- Structure of Recurrent Neural Networks (RNN)
- CNN’s top architectures
- Basic natural language processing techniques

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Course Plan

Lesson 1: Overfitting

1 Fighting overfitting
 1.1 Reducing the network's size
 1.2 Adding weight regularization
 1.3 Adding dropout

Lesson 2: CNN + RNN

1 Understanding recurrent neural networks (RNNs)
 1.1 Our first recurrent layer in Keras
 1.2 A concrete LSTM example in Keras
2 CNN + RNN
 2.1 Creating a dictionary containing all the captions of the images
 2.2 Generator
 2.3 Let's create the model
 2.4 Predict function

Lesson 3: CNNs top architectures

1 Lenet-5 (1998)
2 AlexNet (2012)
3 ZFNet(2013)
4 GoogleNet/Inception(2014)
5 VGGNet (2014)
6 ResNet(2015)
7 Inception V3/ V4
8 Assignment: Do some challenge from Kaggle.com

Lesson 4: NLP

1 Exploring text data using NLTK
 1.1 Counting words
 1.2 Stop words
 1.3 Text normalization
 1.4 n-grams
2 Text classification
 1.1 Binary
 1.2 Multiclass
 1.3 Multilabel
3 Evaluation
 3.1 Precision
 3.2 Recall
 3.3 F1
4 Parts of a speech and meaning
 4.1 Tokenization
 4.2 POS Tagging
 4.3 Chunking and entity recognition

Prerequisites

This course requires a basic understanding of Python. You should either have sat and completed our Python Development Course or already have intermediate-level understanding of Python.

If you have not sat our Python Development course, a Student Affairs Officer will reach out to you upon registration to confirm your mastery of Python.

About this Course:

This course is a specialised version of our Data Science I (Python), designed specifically for the National Data Science Challenge, organized by Shopee. In this course, students will learn advanced Deep Learning and Natural Language Processing techniques to prepare themselves for the advanced category of this challenge: Product Information Extraction

By the end of the course, students will be able to build advanced Deep Learning structures, namely a "classification" or "prediction" engines for product information extraction. Students will also learn to build Deep Learning models with an aim towards product information extraction. All coding and projects will be done in class, under the supervision of the instructor.

Whether you are thinking of registering or have registered for the National Data Science Challenge, joining this course will definitely give you the head start you need.

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