Data Science

TinyML(EdgeAI) in 2025: Machine Learning at the Edge

Applications of edge analytics transforming industries and the edge computing market is expected to reach ~$350 by 2027. However, the current approach to edge analytics involves machine learning models trained on the cloud. This introduces latency to the system and is prone to privacy issues.

Apr 75 min read

Data Science

Web Scraping for Machine Learning: From HTML to ML ['25]

~54.7 billion people around the world have been recorded to use the internet, creating 1.7MB of data every second. Crawling this exponentially growing volume of data could provide many opportunities for breakthroughs in data science.

Apr 44 min read

Data Science

Federated Learning: 5 Use Cases & Real Life Examples ['25]

McKinsey highlights inaccuracy, cybersecurity threats, and intellectual property infringement as the most significant risks of generative AI adoption.Federated learning addresses these challenges by enhancing accuracy, strengthening security, and protecting IP, all while keeping data private.

May 2811 min read

Data Science

Meta Learning: 7 Techniques & Use Cases in 2025

Training and fine-tuning a typical machine learning (ML) model can take weeks and cost thousands. Meta learning helps cut this down by leveraging prior learning experiences to accelerate training, reduce costs, and improve generalization. Explore key meta learning techniques and use cases in fields like healthcare and online learning.

Jun 1111 min read

Data Science

Few-Shot Learning: Methods & Applications in 2025

Imagine a healthcare startup developing an AI system to detect rare diseases, but there’s a problem: there’s not enough labeled data to train a traditional machine learning model. This is where few-shot learning (FSL) comes in.

May 278 min read

Data Science

45 Statistics, Facts & Forecasts on Machine Learning [2025]

Machine learning is the study of computer algorithms that learn through data. Machine learning is regarded as a subset of artificial intelligence. Surveys and market researches are the best way to understand the overall view of the machine learning market because numbers can reveal metrics from the importance of the market to its challenges.

May 276 min read

Data Science

Top 50 Big Data Statistics in 2025: Market Size & Benefits

The driving force behind big data is quantification of information. In the past, you would just go for a morning jog. Today, you know it was 7.6km long, you took 11,341 steps and burned 612 calories because of it.

Jun 165 min read

Data Science

22 AutoML Case Studies: Applications and Results in 2025

Though there is a lot of buzz around autoML, we haven’t found a good compilation of case studies. So we built our comprehensive list of automated machine learning case studies so you can see how autoML could be used in your function/industry.

Apr 103 min read

Data Science

Machine Learning Accuracy: True-False Positive/Negative

Selecting the right metric to evaluate your machine learning classification model is crucial for business success. While accuracy, precision, recall, and AUC-ROC are common measurements, each reveals different aspects of model performance. We’ve analyzed these metrics to help you choose the most appropriate one for your specific use case, ensuring your models deliver real value.

Jun 237 min read

Data Science

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