dockerfile.tar.gz

python3

spa-job

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.

Building Advanced Deep Learning and NLP Projects

## Introduction to the project
Thus far, we have discussed a variety of topics. Remember what we discussed about transfer learning and word2vec. In this project, we are going to use another pre-trained model (embedding): GloVe. This project will use the concepts of transfer learning, embedding, and LSTMs. In this project, we are going to predict an emoji for a particular sentence.

To get started with this project, you will require the following packages. So, first make sure they are installed. You can run the commands below on your local machine.

```shell
pip install emoji
pip install numpy
pip install pandas
pip install keras
```

## Import the packages and load the dataset

You can download the dataset file by clicking the download button shown below. This is a very small dataset and that's the main reason why we are using transfer learning in this project. Once you have the dataset, you can go ahead and import the packages as shown ahead.

# Introduction to the project
Thus far, we have discussed a variety of topics. Remember what we discussed about transfer learning and word2vec. In this project, we are going to use another pre-trained model (embedding): GloVe. This project will use the concepts of transfer learning, embedding, and LSTMs. In this project, we are going to predict an emoji for a particular sentence.

To get started with this project, you will require the following packages. So, first make sure they are installed. You can run the commands below on your local machine.

```shell
pip install emoji
pip install numpy
pip install pandas
pip install keras
```

# Import the packages and load the dataset

You can download the dataset file by clicking the download button shown below. This is a very small dataset and that's the main reason why we are using transfer learning in this project. Once you have the dataset, you can go ahead and import the packages as shown ahead.

In this lesson, we are going to start building our last project in this course based on Transfer Learning in NLP.

Welcome to the Course

Project: Build a COVID-19 Detection System Using X-Rays

Project: Building a Pokemon Classifier Using Transfer Learning

Project: Text Generation Using Markov Chains

Word Embedding: Two Mini Projects

Project: IMDB Reviews Sentiment Analysis

Project: Deciphering Text Using Character-Level RNNs

Project: Emoji Predictor Using Transfer Learning in NLP

Final Exam

Where to Go Next?

Project Creation: Part One

Introduction to the project

Import the packages and load the dataset