What is Explainable AI? In today's data-driven world, artificial intelligence (AI) has revolutionised various aspects of our lives, from healthcare diagnostics to financial risk assessment. However,...
About Neri Van Otten
Neri Van Otten is the founder of Spot Intelligence, a machine learning engineer with over 12 years of experience specialising in Natural Language Processing (NLP) and deep learning innovation. Dedicated to making your projects succeed.
Posts By Neri Van Otten
Universal Sentence Encoder Explained & How To TensorFlow Tutorial
What is a Universal Sentence Encoder? The Universal Sentence Encoder (USE) is a powerful tool in natural language processing (NLP) developed by Google. Its primary function is to transform textual...
LLMOps: What Is It and How To Implement Best Practices
What is LLMOps? The world of artificial intelligence (AI) is constantly evolving, with new advancements emerging at an unprecedented pace. The rise of large language models (LLMs) is among the most...
![Semi-Supervised Machine Learning Made Simple [5 Algorithms & How To Python Tutorial]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2023/12/semi-supervised-machine-learning.jpg?fit=1200%2C675&ssl=1)
Semi-Supervised Machine Learning Made Simple [5 Algorithms & How To Python Tutorial]
What is Semi-Supervised Learning in Machine Learning? Semi-supervised learning is a machine learning paradigm between supervised and unsupervised learning. In this approach, the algorithm learns...
Variational Autoencoders (VAEs) Made Simple & How To TensorFlow Tutorial
What are Variational Autoencoders (VAEs)? Autoencoders are ingenious, unsupervised learning mechanisms capable of learning efficient data representations. However, traditional autoencoders often...
Embeddings from Language Models (ELMo): Contextual Embeddings A Powerful Shift In NLP
What are Embeddings from Language Models (ELMo)? ELMo, short for Embeddings from Language Models, revolutionized the landscape of NLP by introducing contextual embeddings, a paradigm shift from...
![t-SNE Explained: Top 6 Tools & Practical How To Get Started Guide [Python]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2023/12/t-sne-visual-explanation.jpg?fit=1200%2C675&ssl=1)
t-SNE Explained: Top 6 Tools & Practical How To Get Started Guide [Python]
What is t-SNE? t-SNE, or t-distributed Stochastic Neighbor Embedding, is a popular non-linear dimensionality reduction technique used primarily for visualizing high-dimensional data in a...
Data2vec Explained: The Fusion Of Text, Image & Audio To Create Powerful AI Systems
What is Data2vec? Meta AI has introduced Data2vec, a groundbreaking framework for self-supervised learning that transcends the barriers between different data modalities. Data2vec proposes a unified...
Multimodal Natural Language Processing (NLP): The Next Powerful Shift In AI
What is Multimodal NLP? Multimodal NLP refers to the intersection of natural language processing (NLP) with other data or modalities, such as images, videos, audio, and sensor data. Traditional NLP...
![Self-Supervised Learning Made Simple [How To Train Powerful ML Models]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2023/12/pretext-tasks.jpg?fit=1200%2C675&ssl=1)
Self-Supervised Learning Made Simple [How To Train Powerful ML Models]
What is Self-Supervised Learning? Self-supervised learning (SSL) is a machine learning technique where a model learns representations or features directly from the input data without explicit...
![Machine Learning With Graphs Made Simple [& Practical How To Guide]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2023/12/nodes-edges-graph.jpg?fit=1200%2C675&ssl=1)
Machine Learning With Graphs Made Simple [& Practical How To Guide]
What is Machine Learning with Graphs? Machine learning with graphs refers to applying machine learning techniques and algorithms to analyze, model, and derive insights from graph-structured data. In...
Representation Learning Made Simple & Top 10 Machine Learning And Deep Learning Models
What is Representation Learning? Representation learning is a cornerstone in artificial intelligence, fundamentally altering how machines comprehend intricate data. Its core objective lies in...
Prototypical Networks Explained, Compared To Other Networks & How To Tutorial In PyTorch
What is a Prototypical Network? At its core, Prototypical Networks represent a groundbreaking approach to tackling the complexities of classification problems, especially in scenarios where labelled...
![Exploding Gradient Explained: How To Detect & Overcome It [6 Best Practices]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2023/12/exploding-gradient.jpg?fit=1200%2C675&ssl=1)
Exploding Gradient Explained: How To Detect & Overcome It [6 Best Practices]
What is the Exploding Gradient Problem? Neural networks optimize their parameters using gradient-based optimization algorithms like gradient descent. Gradients represent the slope of the loss...
![What Is FastText? Compared To Word2Vec & GloVe [How To Tutorial In Python]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2023/12/continuous-bag-of-words-vs-skip-gram-1.jpg?fit=1200%2C675&ssl=1)
What Is FastText? Compared To Word2Vec & GloVe [How To Tutorial In Python]
What is fastText? fastText, a product of Facebook's AI Research (FAIR) team, represents a remarkable leap forward in natural language processing (NLP). This library, introduced in 2016, builds upon...
Gradient Clipping Explained & Practical How To Guide In Python
What is Gradient Clipping in Machine Learning? Gradient clipping is used in deep learning models to prevent the exploding gradient problem during training. During the training process of neural...
Factor Analysis Made Simple & How To Tutorial In Python
What is Factor Analysis? Factor analysis is a potent statistical method for comprehending complex datasets' underlying structure or patterns. Its primary objective is to condense many observed...
How To Implement GloVe Embeddings In Python: 3 Tutorials & 9 Alternatives
What are GloVe Embeddings? GloVe, or Global Vectors for Word Representation, is an unsupervised learning algorithm that obtains vector word representations by analyzing the co-occurrence statistics...
