Recent Posts by Nisha Shoukath

Detecting Personal Protective Equipment (PPE) Using Machine Learning

There are skyscrapers and architectural marvels all around us. Along with an ever-evolving development in healthcare and major advances in engineering. But we live our daily lives clueless about what it takes to reach this level of progress. With 7.6 million employees and $1.3 trillion in annual expenditure, construction is considered to be one of the largest sectors in the U.S. But it is also the most hazardous industry with a high number of workplace accidents and injuries.

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Machine Learning in Banking – An Overview of Benefits and Possible Use Cases

Machine learning application is growing thanks rapidly to its ability to help businesses automate processes and enhance operations. As the internet proliferates and the need for a growing online presence becomes necessary, companies in various industries increasingly depend on algorithms to decipher complex problems with good assurances toward a solution. Statistics indicate that the machine learning market will grow to $117.19 billion by the end of 2027.

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Common Misconceptions About Data Labeling and Classification

Just like human students need teachers to help them understand educational material, machines require more than just raw data to learn. Data labeling is a key component of a successful machine learning project, but unfortunately, there are some common misconceptions about its importance, how it is done, and who can do it. 

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Artificial Intelligence vs. Machine Learning (AI vs ML)? And What’s the Difference?

Artificial intelligence (AI) and machine learning (ML) are two terms that are coming to the forefront. More organizations are adopting these new technologies, which are now all around us but not always immediately visible. Businesses with e-commerce sites are taking advantage of the ability to increase sales by recommending products based on product images viewed. The healthcare industry is treating patients faster because machines can recognize patterns in high-resolution medical imagery. Manufacturers are improving quality control and catching small errors before they become major issues. 

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Top 8 Natural Language Processing Techniques

Artificial intelligence (AI) encompasses multiple types of machine learning approaches, including computer vision, natural language processing (NLP), audio intelligence, and so on. As the name suggests, NLP is the branch of AI that centers on language and teaching computers how to understand and use it in a natural, human-like manner.

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Twitter Sentiment Analysis Using Machine Learning

Natural Language Processing (NLP) is a popular technology for research and data collection, and sentiment analysis is one of the most common sub-fields of NLP. Sentiment Analysis is the process of analyzing online pieces of writing to predict their emotional tone, i.e. whether a piece of information is positive, negative, or neutral. Tweets on specific topics can be analyzed this way to understand their sentiments.

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Computer Vision Advantages and Disadvantages

Artificial intelligence encompasses several different approaches to solving problems. Computer vision, object detection, natural language processing, and other types of artificial intelligence help businesses and individuals automate processes, improve accuracy, and work more efficiently. The subset of AI known as computer vision centers around visual processing and offers benefits in a range of applications. 

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Understanding 3 Types of Machine Learning Algorithms

Machines learn through algorithms—sets of rules or instructions—that allow them to continually improve through experience. In contrast to programming, which can tell a machine to do a specific task in the same way over and over, machine learning algorithms modify themselves over time based on the original goal set and previous results. 

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10 Benefits of Machine Learning in E-Commerce

No matter what types of products you sell, staying competitive in e-commerce requires constant attention across multiple departments. Sales teams need to know product details, marketing teams must be mindful of popular search terms, product teams must stay on top of trends, and IT teams are responsible for making sure the site is always functional and fast. All of this will always require a certain degree of time and skill, but some tasks, especially the most repetitive ones, can be better handled with machine learning. 

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Getting Started with Machine Learning: Using Browsing Patterns to Determine Buyer Intent

You can do a lot in the back end of a website to make it easier for customers to find products that will interest them. Manually tagging photos, putting products in multiple categories, and adding suggested alternatives are a few of the most common methods for enhancing the buyer’s experience on an e-commerce site. However, this approach has certain limitations, especially for e-commerce businesses that have large inventories or product selections that are continually updated by multiple users.

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