Data science vs machine learning: What is the difference?
Confusion arises when distinguishing between data science and machine learning. This is often due to their interchangeable use in discussions. Individuals struggle to pinpoint the differences and understand how each contributes to data-driven initiatives. This lack of clarity hinders the effective deployment of these technologies within organizations. It can lead to sub-optimal resource utilization and […]
Machine learning vs deep learning: What is the difference?
No longer a distant possibility reserved for futuristic sci-fi novels, AI is reshaping the world around us. Artificial intelligence models can perform at the same speed and complexity as humans. In healthcare, AI analyzes decades of patient data to detect diseases earlier. In pharmaceuticals, AI can simulate drug trials and discover new life-saving medicines. Research […]
Machine learning vs AI: What is the difference?
Artificial intelligence (AI) and machine learning (ML) are often used interchangeably. However, these disciplines each have unique distinctions within the realm of advanced computing. AI is a broad discipline focused on developing systems capable of performing tasks to a similar level to human intelligence. ML is a dedicated subset of AI. It specializes in creating […]
Types of machine learning models explained
Machine learning (ML) technologies unveil an exciting new layer of modern computational capabilities. Decades of research and development in both computer and data sciences have led to the rise of machine-learning models. These ML models can now emulate a high degree of intelligence similar to that of humans to perform complex tasks and actions. This […]
Top 11 machine learning algorithms
Decades of development in data and computer science are catapulting AI capabilities to new heights. Natural language processing (NLP) enables generative chatbots like ChatGPT and Google Gemini to engage users in conversational interactions. Machine learning (ML) algorithms leverage big data to predict patterns and accurately complete tasks. This article will focus on a key subset […]
What are AI ethics? Definition, principles, and examples
The potential of AI has left the realm of sci-fi cinema and continues to impact the real world. AI-driven chatbots like ChatGPT and Google Gemini have seen user bases reach millions worldwide. Machine learning (ML) and natural language understanding (NLU) enable these tools to have fluid, intuitive conversations capable of handling complex demands. However, the […]
50 Machine learning interview questions + tips
Artificial intelligence (AI) continues to fast-track modern tech capabilities. Decades of research and developments in data and computer science have enabled these wins. Within this exciting field sits machine learning (ML). This dedicated discipline trains machines to emulate or even outperform human intelligence based on input data. Potential application areas for ML solutions are driving […]
The ultimate guide to Salesforce implementation
Salesforce is a powerful CRM tool for global sales teams, especially in the US. It allows organizations to interact effectively with customers to meet and predict their needs. In 2023, Salesforce CRM had a global market share of 21.7%, making it the number one CRM available. Given these statistics, it’s impossible not to consider how […]
17 Great technical writing examples
Your products are of little value to customers unless they know how to use them. Technical writing has the potential to promote product stickiness and digital adoption of new technologies. Your business plans need specific and technical expertise to record them correctly so they are easy to follow and can drive digital transformation. The number […]
Generative AI vs large language models: What is the difference?
Generative AI and large language models (LLMs) go hand in hand, but only if you know the differences. In 2023, almost a third of companies were using generative AI in some form. In contrast, 58% of companies in the same year began experimenting with large language models, but only 23% planned to implement them soon. […]