Machine Learning

Machine learning extracts information from data that is not apparent to even experienced business users. Data scientists normally spearhead this process using specialized data science tools such as Python and R, but Business users are most times limited to static ML output and reports. InetSoft changes that.

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Productionalize Machine Learning for Visual Analysis

InetSoft's data intelligence software productionalizes machine learning. It provides visual tools that directly tap into machine learning business applications. Business users can not only visually analyze machine learning results but also train machine learning models with sliced-and-diced data.

When data grows beyond an experimental machine learning setup, InetSoft's native Apache Spark based platform can easily scale on demand. It can utilize an external Spark Cluster or build its own with minimal Spark expertise.

machine learning model train dashboard example

Mashup Human and Machine Intelligence

Machine learning is a great new tool for many business applications. But just like other business data, it's most powerful when it is combined with other data and analysis.

InetSoft's data intelligence is based on a powerful mashup engine. With productionalized machine learning that business users can directly access, machine learning output can also be effortlessly mashed up with human designed analysis.

machine learning mashup dashboard example

Is Machine Learning Being Supplanted by Artificial Intelligence?

The relationship between machine learning (ML) and artificial intelligence (AI) is often misunderstood, leading to misconceptions about whether one is supplanting the other. In reality, machine learning is a subset of artificial intelligence, representing a specific approach to achieving AI. While machine learning techniques have gained significant traction in recent years, particularly with advancements in deep learning, it is incorrect to suggest that machine learning is replacing artificial intelligence altogether.

Machine learning involves the use of algorithms and statistical models to enable computer systems to perform tasks without explicit programming. It relies on the analysis of data to identify patterns, learn from examples, and make predictions or decisions. While machine learning is a powerful tool for solving a wide range of problems, including image recognition, natural language processing, and predictive analytics, it is just one component of the broader field of artificial intelligence.

Artificial intelligence encompasses a broader set of technologies and approaches aimed at creating systems that can mimic human intelligence and perform tasks that typically require human cognitive abilities, such as reasoning, problem-solving, and understanding language. While machine learning is a key technique within artificial intelligence, AI also encompasses other methods such as expert systems, symbolic reasoning, and evolutionary algorithms, among others.

Rather than being supplanted by machine learning, artificial intelligence is evolving alongside it, with machine learning techniques playing a central role in many AI applications. As advancements in machine learning continue to drive progress in areas such as autonomous vehicles, healthcare, and finance, artificial intelligence as a whole is becoming increasingly capable and pervasive in our society.

More Resources About Machine Learning

Automate Insights From Complex Data - Supervised learning is just that, learning that requires supervision. Algorithms in this category utilize your established variable prediction model and train a ML predictor variable against it to make future calculations...

Ensuring an Efficient Machine Learning Process - By automating time-consuming operations such as data collection, information organization, and trend reporting, machine learning solutions can boost productivity and efficiency. All of those jobs, even with enormous amounts of data, may be completed instantly thanks to machine learning business applications. The machine learning process takes several steps, each of which can benefit greatly from data visualization...

How the Machine Learning Approach Works - With the machine learning approach, instead of writing a program by hand for each specific task, for a particular task we collect a lot of examples that specify the correct output for giving an input. The machine learning algorithm then takes these examples and produces a program that does the job. The program produced by the learning algorithm may look very different from a typical handwritten program...

Inspiring Machine Learning Applications - To enhance its content curation capabilities, social media giant Pinterest adopted an Ml-driven business intelligence system that specializes in working with data to assist the platform in its content discovery and recommendation strategy...