Understanding Stochastic Gradient Descent (SGD) In Machine Learning Stochastic Gradient Descent (SGD) is a pivotal optimization algorithm widely utilized in machine learning for training models....
The Natural Language Processing (NLP) Blog
Topic: Data Science
The Cold-Start Problem In Machine Learning Explained & 6 Mitigating Strategies
What is the Cold-Start Problem in Machine Learning? The cold-start problem refers to a common challenge encountered in machine learning systems, particularly in recommendation systems, where the...
![Knowledge Graph Reasoning Made Simple [3 Technical Methods & How To Handle Uncertanty]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2024/02/query2vec.jpg?fit=1200%2C675&ssl=1)
Knowledge Graph Reasoning Made Simple [3 Technical Methods & How To Handle Uncertanty]
What is Knowledge Graph Reasoning? Knowledge Graph Reasoning refers to drawing logical inferences, making deductions, and uncovering implicit information within a knowledge graph. A knowledge graph...
Computational Linguistics: An Easy Explanation With Examples, Advancements & Future Trends
What is Computational Linguistics? Computational linguistics is an interdisciplinary field that combines principles of linguistics and computer science to develop computational models and algorithms...
Link Prediction For Graph Neural Networks (GNN) Made Simple & 6 Powerful Tools
What is Link Prediction Based on Graph Neural Networks? Link prediction, a crucial aspect of network analysis, is the predictive compass guiding our understanding of complex relationships within...
Entity Resolution Explained: Top 12 Techniques, Practical Guide & 5 Pythons/R Libraries
What is Entity Resolution? Entity resolution, also known as record linkage or deduplication, is a process in data management and data analysis where records that correspond to the same entity across...
Node2Vec: Extensive Guide & How To Tutorial In Python
What is Node2Vec? Node2Vec is a popular algorithm for learning continuous representations (embeddings) of nodes in a graph. It is a technique in network representation learning, which involves...
Knowledge Representation And Reasoning In Artificial Intelligence (AI) Made Simple
What is Knowledge Representation and Reasoning (KRR)? Knowledge Representation and Reasoning (KRR) are fundamental concepts in artificial intelligence (AI) that focus on how intelligent systems can...
![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...
![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...
![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...
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 Build Content-Based Recommendation System Made Easy [Top 8 Algorithms & Python Tutorial]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2023/11/content-based-recommendation-system.jpg?fit=1200%2C675&ssl=1)
How To Build Content-Based Recommendation System Made Easy [Top 8 Algorithms & Python Tutorial]
What is a Content-Based Recommendation System? A content-based recommendation system is a sophisticated breed of algorithms designed to understand and cater to individual user preferences by...
Knowledge Graph: How To Tutorial In Python, LLM Comparison & 23 Tools & Libraries
What is a Knowledge Graph? A Knowledge Graph is a structured representation of knowledge that incorporates entities, relationships, and attributes to create a network of interconnected...
Independent Component Analysis (ICA) Made Simple & How To Tutorial In Python
What is Independent Component Analysis (ICA)? Independent Component Analysis (ICA) is a powerful and versatile technique in data analysis, offering a unique perspective on the exploration and...
Linear Discriminant Analysis Made Simple & How To Tutorial In Python
What is Linear Discriminant Analysis (LDA)? Linear Discriminant Analysis (LDA) is a powerful technique in machine learning and statistics. It is primarily used for dimensionality reduction and...
