What Are Autoregressive (AR) Models? Autoregressive (AR) models are statistical and time series models used to analyze and forecast data points based on their previous values. These models are...
The Natural Language Processing (NLP) Blog
Topic: Deep Learning
![Pre-Trained Models Complete Guide [How To & 21 Top Models In PyTorch, TensorFlow & HuggingFace]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2023/10/pre-trained-models.jpg?fit=960%2C540&ssl=1)
Pre-Trained Models Complete Guide [How To & 21 Top Models In PyTorch, TensorFlow & HuggingFace]
Understanding Pre-Trained Models Pre-trained models have become a game-changer in artificial intelligence and machine learning. They offer a shortcut to developing highly capable models for various...
Teacher Forcing In Recurrent Neural Networks (RNNs): An Advanced Concept Made Simple
What is teacher forcing? Teacher forcing is a training technique commonly used in machine learning, particularly in sequence-to-sequence models like Recurrent Neural Networks (RNNs) and...
Mode Collapse In GANs Explained, How To Detect It & Practical Solutions
What is mode collapse in Generative Adversarial Networks (GANs)? Mode collapse is a common issue in generative models, particularly in the context of generative adversarial networks (GANs) and some...
Continual Learning Made Simple, How To Get Started & Top 4 Models
The need for continual learning In the ever-evolving landscape of machine learning and artificial intelligence, the ability to adapt and learn continuously (continual learning) has become...
Sequence-to-Sequence Architecture Made Easy & How To Tutorial In Python
What is sequence-to-sequence? Sequence-to-sequence (Seq2Seq) is a deep learning architecture used in natural language processing (NLP) and other sequence modelling tasks. It is designed to handle...
Cross-Entropy Loss — Crucial In Machine Learning — Complete Guide & How To Use It
What is cross-entropy loss? Cross-entropy Loss, often called "cross-entropy," is a loss function commonly used in machine learning and deep learning, particularly in classification tasks. It...
Natural Language Generation Explained & 2 How To Tutorials In Python
What is natural language generation? Natural Language Generation (NLG) is a subfield of artificial intelligence (AI) and natural language processing (NLP) that focuses on the automatic generation of...
Top 8 Loss Functions Made Simple & How To Implement Them In Python
What are loss functions? Loss functions, also known as a cost or objective functions, are critical component in training machine learning models. It quantifies a machine learning model's performance...
How To Implement Cross-lingual Transfer Learning In 5 Different Ways
What is cross-lingual transfer learning? Cross-lingual transfer learning is a machine learning technique that involves transferring knowledge or models from one language to another, typically to...
Practical Guide To Doc2Vec & How To Tutorial In Python
In today's data-driven world, making sense of vast volumes of text data is paramount. Natural Language Processing (NLP) techniques are at the forefront of unlocking the insights hidden within text,...
Understanding Dropout in Neural Network: Enhancing Robustness and Generalization
What is dropout in neural networks? Dropout is a regularization technique used in a neural network to prevent overfitting and enhance model generalization. Overfitting occurs when a neural network...
![Multi-class Classification Explained With 3 How To Python Tutorials [Scikit-Learn, PyTorch & Keras]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2023/08/multi-class-classification.jpg?fit=1200%2C675&ssl=1)
Multi-class Classification Explained With 3 How To Python Tutorials [Scikit-Learn, PyTorch & Keras]
What is multi-class classification in machine learning? Multi-class classification is a machine learning task that aims to assign input data points to one of several predefined classes or...
![Deep Dive into Active Learning in Machine Learning [How To In Python & PyTorch]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2023/08/active-learning-try-fail.jpg?fit=1200%2C675&ssl=1)
Deep Dive into Active Learning in Machine Learning [How To In Python & PyTorch]
What is active learning in machine learning? Active learning is a machine learning technique that involves iteratively selecting and labelling the most informative examples from an unlabeled dataset...
What Is A Large Language Model? Use Cases, Benefits, Limitations & What Does The Future Hold?
What is a large language model? A large language model (LLM) is a type of artificial intelligence (AI) trained on massive text and code datasets. This allows them to learn the patterns and...
![Zero-shot Classification [Top 6 Models, How To Tutorial In Python & Alternatives]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2023/08/zero-shot-classification.jpg?fit=1200%2C675&ssl=1)
Zero-shot Classification [Top 6 Models, How To Tutorial In Python & Alternatives]
What is zero-shot classification? Zero-shot classification is a machine learning approach in which a model can classify data into multiple classes without any specific training examples for those...
Graph Neural Network Explained & How To Tutorial In Python With PyTorch
Graph Neural Network (GNN) is revolutionizing the field of machine learning by enabling effective modelling and analysis of structured data. Originally designed for graph-based data, GNNs have found...
Activation Function: Top 9 Most Popular Explained & When To Use Them
What is an activation function? In artificial neural networks, an activation function is a mathematical function that introduces non-linearity to the output of a neuron or a neural network layer. It...
