These days, terms like data science, machine learning and artificial intelligence are sometimes mentioned interchangeably, albeit incorrectly. Even an organization offering a new technology powered by any of these may talk about their high-end data science techniques without having much knowledge about them.
Did you know that the artificial intelligence market is expected to grow at a CAGR (compound annual growth rate) of a whopping 52% from 2017 to 2025? The term, what was coined by John McCarthy in 1953, has become one of the most crucial parts of our daily lives and in the business environment these days. In today’s tech-driven world, a lot of work is being done by software and machines and these can be heavily attributed to artificial intelligence. In this post, we’re going to see how this field has enabled us to achieve highs that were unthinkable without it.
The data science spectrum has exponentially evolved over the last few years and today it’s considered the backbone of a huge number of businesses across industries. More and more people are trying to step into this field observing the skyrocketing popularity of data science. As a result, lots of institutes have started offering different data science courses to make students ready for the field. But here’s the biggest question – how would you figure out whether an institute is worth joining? In this post we’re going to take a look at Magnimind Academy – the premium data science institute headquartered in CA and some of the major reasons for which a huge number of students consider this their first preference.
Most likely you have already come across the term blockchain which is taking the tech world by storm these days. Put simply, blockchain can be considered as a digital ledger where facts are kept in data blocks. These data blocks are connected to each other through cryptographic validation. The entire system leads to an immutable record of data which is managed by a cluster of computers. Let’s see some most common use cases of blockchain to understand why experts call it one of the biggest disrupting innovations ever.
Artificial intelligence together with its most talked about subcategory machine learning are probably the biggest two factors impacting the entire business world and transforming it. We may not always realize how these technologies are involved in our day-to-day life, but in reality, they’re present in a lot of aspects. In a business context, almost every industry leverages the power of artificial intelligence and machine learning – from traveling industry to transportation industry to the healthcare industry and many more. In this post, we’re going to explore the impacts of these two technologies on the finance industry.
These days, lots of companies are implementing the blockchain technology with the hope of discovering opportunities to create differences in their regular business process. Unfortunately, a lot of these implementations never get past of the production stage. While the technology comes with lots of potential enough to attract business leaders, there’s a significant gap between that hype and market reality. If you too are thinking of implementing blockchain technology, here’re nine of the most common mistakes and ways to avoid them.
Undeniably, artificial intelligence has become one of the most talked-about areas of the IT domain. The demand for artificial intelligence developers is growing rapidly and professionals from different industries, as well as, beginners are trying to step into this field. Though there’re people who imagine a future where machines replace humans, it’s probably the best time to learn this technology as it’ll change the future of the tech domain drastically. If you’re a beginner and looking to become an artificial intelligence developer, here’re the most effective ways you should follow.
In the U.S., over 36,000 weather forecasts are issued every day that cover 800 different areas and cities. Though some people may complain about the inaccuracy of such forecasts when a sudden spell of rain messes with their picnic or outdoor sports plan, not many spare a thought about how accurate such forecasts often are. That’s exactly what the people at Forecastwatch.com (a leader in climate intelligence and business-critical weather) did. They assembled all 36,000 forecasts, placed them in a database, and compared them to the actual conditions that existed on that particular day in that specific location. Forecasters around the country then take advantage of these results to improve their forecast models for the subsequent round. Those at Forecastwatch used Python to write a parser for collecting forecasts from other websites, an aggregation engine to assemble the data, and the website code to show the results. Though the company originally used PHP to build the website, it soon realized that it was much easier to only deal with a solitary language throughout. And there lies the beauty of Python, which has become essential for data analysis. Let’s delve deeper to understand what makes Python so popular in the field of data analysis.
Undeniably, both the terms artificial intelligence and machine learning belong to the most-used buzzwords these days. Almost every tech organization is using these terms when talking about their products or services. Unfortunately, there’re still lots of confusion within the common people about what are these two exactly. Let’s go through the key differences between artificial intelligence and machine learning.
Most likely you’ve already heard or read the term blockchain somewhere and know there is a huge buzz going around it in the technology domain. The technology that was invented to power Bitcoin in 2008, is now being used for almost everything. However, despite all the news and predictions are made around it by experts, it seems that a lot of people aren’t much aware of what blockchain actually is, what are the key advantages of using it and what are its biggest features? In this post, we’re going to explore all these things about blockchain and why you should learn this technology. Let’s delve deeper.