Top 7 ways of implementing data augmentation for both images and text. With the top 3 libraries in Python to use for...
The Natural Language Processing (NLP) Blog
Machine Learning – Deep Learning – Data Science
Understanding Generative Adversarial Network With A How To Tutorial In TensorFlow And Python
What is a Generative Adversarial Network (GAN)? What are they used for? How do they work? And what different types are...
Autoencoder Made Easy — Variations, Applications, Tutorial in Python With TensorFlow
Autoencoder variations explained, common applications and their use in NLP, how to use them for anomaly detection and...
Adam Optimizer Explained & Top 3 Ways To Implement In Python With Keras, Pytorch & TensorFlow
Explanation, advantages, disadvantages and alternatives of Adam optimizer with implementation examples in Keras,...
![What Is Overfitting & Underfitting [How To Detect & Overcome In Python]](https://spotintelligence.com/wp-content/uploads/2023/02/overfitting-underfitting.jpg)
What Is Overfitting & Underfitting [How To Detect & Overcome In Python]
Illustrated examples of overfitting and underfitting, as well as how to detect & overcome them Overfitting and...
Backpropagation Made Easy With Examples And How To In Python With Keras
Why is backpropagation important in neural networks? How does it work, how is it calculated, and where is it used?...
How To Implement Logistic Regression Text Classification In Python With Scikit-learn and PyTorch
Text classification is a fundamental problem in natural language processing (NLP) that involves categorising text data...
Restricted Boltzmann Machines Explained & How To Tutorial In Python
How are RBMs used in deep learning? Examples, applications and how it is used in collaborative filtering. With a...
SMOTE Oversampling & Tutorial On How To Implement In Python And R
How does the algorithm work? What are the disadvantages and alternatives? And how do we use it in machine learning?...
![Tutorial TF-IDF vs Word2Vec For Text Classification [How To In Python With And Without CNN]](https://spotintelligence.com/wp-content/uploads/2023/02/word2vec-text-classification-jpg.webp)
Tutorial TF-IDF vs Word2Vec For Text Classification [How To In Python With And Without CNN]
Word2Vec for text classification Word2Vec is a popular algorithm used for natural language processing and text...
Fuzzy Logic Made Easy — Its Application In AI, Machine Learning & Natural Language Processing (NLP)
What is fuzzy logic? Fuzzy logic is a mathematical approach to reasoning about uncertain or vague information. Rather...
Deep Belief Network — Explanation, Application & How To Get Started In TensorFlow
How does the Deep Belief Network algorithm work? Common applications. Is it a supervised or unsupervised learning...
Top 10 Natural Language Processing (NLP) Research Papers For Beginners
Reading research papers is integral to staying current and advancing in the field of NLP. Research papers are a way to...
The Vanishing Gradient Problem, How To Detect & Overcome It
When does it occur? How can you recognise it? And how to adapt your network to avoid the vanishing gradient problem....
Understanding Elman RNN — Uniqueness & How To Implement In Python With PyTorch
What is the Elman neural network? Elman Neural Network is a recurrent neural network (RNN) designed to capture and...
Self-attention Made Easy And How To Implement It In PyTorch
Self-attention is the reason transformers are so successful at many NLP tasks. Learn how they work, the different...
Gated Recurrent Unit Explained & How They Compare LSTM, RNN & CNN
What is a Gated Recurrent Unit? A Gated Recurrent Unit (GRU) is a Recurrent Neural Network (RNN) architecture type. It...
Top 9 Ways To Implement Text Normalization Techniques In NLP With Python
Text normalization is a key step in natural language processing (NLP). It involves cleaning and preprocessing text...
