Machine Learning University: Accelerated Natural Language Processing Class

Overview

logo

Machine Learning University: Accelerated Natural Language Processing Class

This repository contains slides, notebooks and datasets for the Machine Learning University (MLU) Accelerated Natural Language Processing class. Our mission is to make Machine Learning accessible to everyone. We have courses available across many topics of machine learning and believe knowledge of ML can be a key enabler for success. This class is designed to help you get started with Natural Language Processing (NLP), learn widely used techniques and apply them on real-world problems.

YouTube

Watch all NLP class video recordings in this YouTube playlist from our YouTube channel.

Playlist

Course Overview

There are three lectures and one final project in this class. Course overview is below.

Lecture 1 Lecture 2 Lecture 3
Introduction to ML Tree-based Models Neural Networks
Intro to NLP and Text Processing Regression Models Word Embeddings
Bag of Words (BoW) Optimization-Regularization Recurrent Neural Networks (RNN)
K Nearest Neighbors (KNN) Hyperparameter Tuning Transformers
AWS AI/ML Services

Final Project: Practice working with a "real-world" NLP dataset for the final project. Final project dataset is in the data/final_project folder. For more details on the final project, check out this notebook.

Contribute

If you would like to contribute to the project, see CONTRIBUTING for more information.

License

The license for this repository depends on the section. Data set for the course is being provided to you by permission of Amazon and is subject to the terms of the Amazon License and Access. You are expressly prohibited from copying, modifying, selling, exporting or using this data set in any way other than for the purpose of completing this course. The lecture slides are released under the CC-BY-SA-4.0 License. The code examples are released under the MIT-0 License. See each section's LICENSE file for details.

Owner
AWS Samples
AWS Samples
GAM timeseries modeling with auto-changepoint detection. Inspired by Facebook Prophet and implemented in PyMC3

pm-prophet Pymc3-based universal time series prediction and decomposition library (inspired by Facebook Prophet). However, while Faceook prophet is a

Luca Giacomel 314 Dec 25, 2022
Extended Isolation Forest for Anomaly Detection

Table of contents Extended Isolation Forest Summary Motivation Isolation Forest Extension The Code Installation Requirements Use Citation Releases Ext

Sahand Hariri 377 Dec 18, 2022
Simple structured learning framework for python

PyStruct PyStruct aims at being an easy-to-use structured learning and prediction library. Currently it implements only max-margin methods and a perce

pystruct 666 Jan 03, 2023
The Simpsons and Machine Learning: What makes an Episode Great?

The Simpsons and Machine Learning: What makes an Episode Great? Check out my Medium article on this! PROBLEM: The Simpsons has had a decline in qualit

1 Nov 02, 2021
PyTorch extensions for high performance and large scale training.

Description FairScale is a PyTorch extension library for high performance and large scale training on one or multiple machines/nodes. This library ext

Facebook Research 2k Dec 28, 2022
Open-Source CI/CD platform for ML teams. Deliver ML products, better & faster. āš”ļøšŸ§‘ā€šŸ”§

Deliver ML products, better & faster Giskard is an Open-Source CI/CD platform for ML teams. Inspect ML models visually from your Python notebook šŸ“— Re

Giskard 335 Jan 04, 2023
Timeseries analysis for neuroscience data

=================================================== Nitime: timeseries analysis for neuroscience data ===============================================

NIPY developers 212 Dec 09, 2022
Machine Learning Techniques using python.

šŸ‘‹ Hi, I’m Fahad from TEXAS TECH. šŸ‘€ I’m interested in Optimization / Machine Learning/ Statistics 🌱 I’m currently learning Machine Learning and Stat

FAHAD MOSTAFA 1 Jan 19, 2022
Implementation of linesearch Optimization Algorithms in Python

Nonlinear Optimization Algorithms During my time as Scientific Assistant at the Karlsruhe Institute of Technology (Germany) I implemented various Opti

Paul 3 Dec 06, 2022
Metric learning algorithms in Python

metric-learn: Metric Learning in Python metric-learn contains efficient Python implementations of several popular supervised and weakly-supervised met

1.3k Dec 28, 2022
BASTA: The BAyesian STellar Algorithm

BASTA: BAyesian STellar Algorithm Current stable version: v1.0 Important note: BASTA is developed for Python 3.8, but Python 3.7 should work as well.

BASTA team 16 Nov 15, 2022
SmartSim makes it easier to use common Machine Learning (ML) libraries like PyTorch and TensorFlow

SmartSim makes it easier to use common Machine Learning (ML) libraries like PyTorch and TensorFlow, in High Performance Computing (HPC) simulations and workloads.

Compare MLOps Platforms. Breakdowns of SageMaker, VertexAI, AzureML, Dataiku, Databricks, h2o, kubeflow, mlflow...

Compare MLOps Platforms. Breakdowns of SageMaker, VertexAI, AzureML, Dataiku, Databricks, h2o, kubeflow, mlflow...

Thoughtworks 318 Jan 02, 2023
The unified machine learning framework, enabling framework-agnostic functions, layers and libraries.

The unified machine learning framework, enabling framework-agnostic functions, layers and libraries. Contents Overview In a Nutshell Where Next? Overv

Ivy 8.2k Dec 31, 2022
Relevance Vector Machine implementation using the scikit-learn API.

scikit-rvm scikit-rvm is a Python module implementing the Relevance Vector Machine (RVM) machine learning technique using the scikit-learn API. Quicks

James Ritchie 204 Nov 18, 2022
SPCL 48 Dec 12, 2022
Graphsignal is a machine learning model monitoring platform.

Graphsignal is a machine learning model monitoring platform. It helps ML engineers, MLOps teams and data scientists to quickly address issues with data and models as well as proactively analyze model

Graphsignal 143 Dec 05, 2022
Implementation of different ML Algorithms from scratch, written in Python 3.x

Implementation of different ML Algorithms from scratch, written in Python 3.x

Gautam J 393 Nov 29, 2022
YouTube Spam Detection with python

YouTube Spam Detection This code deletes spam comment on youtube videos based on two characteristics (currently) If the author of the comment has a se

MohamadReza Taalebi 5 Sep 27, 2022
MaD GUI is a basis for graphical annotation and computational analysis of time series data.

MaD GUI Machine Learning and Data Analytics Graphical User Interface MaD GUI is a basis for graphical annotation and computational analysis of time se

Machine Learning and Data Analytics Lab FAU 10 Dec 19, 2022