Skip to content
Machine Learning Explained, Machine Learning Tutorials

MachineCurve

  • About MachineCurve
  • Articles
    • Deep learning
    • Other ML techniques
    • Frameworks
    • Applied AI
  • Ask Questions
  • Collections
    • About the Collections project
    • Dissecting Deep Learning (work in progress)
    • Mastering TensorFlow & Keras
    • Mastering PyTorch
    • Mastering Scikit-learn
    • HuggingFace Transformers
  • Newsletter

Tag: Machine Learning

Easy Named Entity Recognition with Machine Learning and HuggingFace Transformers

Easy Named Entity Recognition with Machine Learning and HuggingFace Transformers

Chris11 February 202112 February 2021Leave a comment
Deep learning approaches have boosted the field of Natural Language Processing in recent years. A variety of tasks can now...
Read More
How to save and load a PyTorch model?

How to save and load a PyTorch model?

Chris3 February 20213 February 2021Leave a comment
You don’t train deep learning models without using them later. Instead, you want to save them, in order to load...
Read More
How to use K-fold Cross Validation with PyTorch?

How to use K-fold Cross Validation with PyTorch?

Chris3 February 202115 February 20216 Comments
Machine learning models must be evaluated with a test set after they have been trained. We do this to ensure...
Read More
Testing PyTorch and Lightning models

Testing PyTorch and Lightning models

Chris27 January 202127 January 2021Leave a comment
Model evaluation is key in validating whether your machine learning or deep learning model really works. This procedure, where you...
Read More
Creating a Multilayer Perceptron with PyTorch and Lightning

Creating a Multilayer Perceptron with PyTorch and Lightning

Chris26 January 202126 January 20214 Comments
Multilayer Perceptrons or MLPs are one of the basic types of neural networks that can be created. Still, they are...
Read More
Using ReLU, Sigmoid and Tanh with PyTorch, Ignite and Lightning

Using ReLU, Sigmoid and Tanh with PyTorch, Ignite and Lightning

Chris21 January 202121 January 2021Leave a comment
Rectified Linear Unit, Sigmoid and Tanh are three activation functions that play an important role in how neural networks work....
Read More
Binary Crossentropy Loss with PyTorch, Ignite and Lightning

Binary Crossentropy Loss with PyTorch, Ignite and Lightning

Chris20 January 202120 January 2021Leave a comment
Training a deep learning model is a cyclical process. First, you feed forward data, generating predictions for each sample. Then,...
Read More
Object Detection for Images and Videos with TensorFlow 2.0

Object Detection for Images and Videos with TensorFlow 2.0

Chris15 January 202118 January 2021Leave a comment
Object detection is one of the areas in Deep Learning where much progress has been made. Using a variety of...
Read More
Getting started with PyTorch

Getting started with PyTorch

Chris13 January 202120 January 2021Leave a comment
When you want to build a deep learning model these days, there are two machine learning libraries that you must...
Read More
Using SELU with TensorFlow 2.0 and Keras

Using SELU with TensorFlow 2.0 and Keras

Chris12 January 202120 January 2021Leave a comment
Neural networks thrive on nonlinear data only when nonlinear activation functions are used. The Rectified Linear Unit, or RELU, is...
Read More

Posts navigation

1 2 … 11

Disclaimer

Although we make every effort to always display relevant, current and correct information, we cannot guarantee that the information meets these characteristics.

Privacy Policy

Stay up to date about ML developments 👨‍🎓

We post new blogs every week. Sign up to learn new things and better understand concepts you already know. We send emails every Friday.

By signing up, you consent that any information you receive can include services and special offers by email.

Follow MachineCurve.com

MachineCurve
Proudly powered by WordPress | Theme: refur by Crocoblock.
Show Buttons
Hide Buttons