With the ever-growing scope of tech and engineering, machine learning has set its reputation as one of the most advanced and revolutionary fields today. As a result, it’s also known as one of the most demanding subjects to learn professionally. That’s a fair observation, considering how rapidly AI and machine learning are taking over every industry, with new, intelligent, automated technologies raising the standards every other week.
As intimidating as this branch of data science may be, anyone can learn it today with the right tools, resources, and guidance. So, let’s break down this subject line-by-line to figure out why machine learning is so hard, why it matters, what the machine learning definition is, and what’s the easiest way to start taking AI lessons today.
What is AI and Machine Learning?
Contrary to popular belief, AI and machine learning are not exactly the same. Rather, machine learning is one of the many subcategories of AI.
As the name suggests, machine learning means duplicating the learning mechanisms of a human brain for a computer. In other words, it refers to teaching a program how to analyze and manipulate data independently without human input. What kind of data, you might ask? Pretty much anything can be structured into a digital format, text, images, videos, audio, and much more. Since mastering online chess games, this innovative branch of AI has come a long way, as it now provides accurate text translations, safe travel routes, and much more.
You have to train your model by feeding it a truckload of sample data. Then, you must point out different connections and patterns in each dataset to create deep algorithms for your model, which the program will use to make informed decisions.
Of course, that’s an oversimplification, and as a professional data scientist will tell you, expertise in this field goes far beyond the basics and requires a firm grip on various data manipulation languages, including NLP, MySQL, and Python. Suffice it to say, there’s a lot to cover in this subject over the general definition, and the best way to keep learning this without overload is with a guided expert by your side.
Fortunately, Superprof’s got hundreds of them. This leading platform for online private education offers some of the best machine-learning tutors. They’ve got the knowledge and experience for applying ML and teaching it to beginners and pros of all ages – including you. So, sign up for Superprof and enter the digital age of tomorrow.
Does AI and Machine Learning Matter?
If you’re new to ML, you may wonder if this complicated subject is worth learning. Sure, it’s an advanced field, but if machine learning is as challenging as they say, it might not be applicable out there, right?
Well, that couldn’t be further from the truth. Almost every aspect of the internet uses machine learning in one way or another. 72% of executives claim that AI and ML will be the greatest advantage for businesses in the future, and the proof of this prediction speaks for itself. From speech recognition to user feed customization, machine learning has played a critical role in creating an automated and personalized internet experience that we know and love today.
Gmail utilizes ML algorithms to mark spam emails in your inbox. Pinterest and TikTok keep track of what you search, watch, like, share, and use ML models to recommend similar content accordingly. Google Maps was trained upon millions of visual datasets to guide users to safer and faster navigation routes efficiently. Siri, Alexa, and other customer service chatbots are all taught through ML and other extensive AI technologies.
But all this doesn’t even scratch the surface of how many industries have evolved thanks to machine learning. Here’re a few examples to broaden your perception:
| Band | Best-Known Albums | Years Active |
|---|---|---|
| The Beatles | Sgt. Pepper's Lonely Hearts Club Band, Abbey Road | 1960–1970 |
| The Rolling Stones | Sticky Fingers, Exile on Main St. | 1962–present |
| The Kinks | The Village Green Preservation Society, Lola Versus Powerman and the Moneygoround, Part One | 1964–1996 |
| The Clash | London Calling, Combat Rock | 1976–1986 |
| Pink Floyd | The Dark Side of the Moon, The Wall | 1965–1995, 2012–2014 |
| Queen | A Night at the Opera, The Game | 1970–1991 (with Freddie Mercury), 2004–present (as Queen +) |
| Fleetwood Mac | Rumours, Tusk | 1967–present |
| The Smiths | The Queen Is Dead, Meat Is Murder | 1982–1987 |
| Radiohead | OK Computer, Kid A | 1985–present |
| Blur | Parklife, 13 | 1988–present (intermittently) |
| Oasis | Definitely Maybe, (What’s the Story) Morning Glory? | 1991–present (intermittently) |
| Arctic Monkeys | Whatever People Say I Am, That’s What I’m Not, AM | 2002–present |
These examples highlight how machine learning is slowly bringing automation, customization, and personalization to all realms of technology, and these applications will only expand in the future. The AI industry is predicted to have a demand of 97 million people by 2025. There are numerous machine learning benefits.
But it’s not just about improving machines and creating apps. Machine learning lessons can charge up your skillset as well. You’ll gain a much deeper understanding of data analysis and interpretation, which can open a new world of critical thinking and problem-solving in many aspects of your life. Moreover, there will be a significant increase in machine learning jobs in the near future.
What Makes Learning Machine Learning Difficult?
Is machine learning difficult? Undoubtedly, but what makes it so complex?
Since machine learning is built upon some of the most advanced computer science concepts, you should at least have a base knowledge of common data visualization languages like Python and MySQL. As you dig deeper into these languages, you’ll have to learn about complex algorithms and the time and patience needed to experiment with them repeatedly.
Your grip on mathematics should also be pretty solid, as most ML concepts use calculus, algebra, statistics, probability, and other logic-focused principles. Math doesn’t exactly have a reputation among the easy subjects, so being proficient in it directly prepares you for some of the more tedious parts of machine learning.
Most aspiring learners aren’t interested in learning base concepts or core languages. They skip the prerequisites and jump straight to the lessons, and as a result, they quickly get lost and confused when they study a concept out of their league.
If you think you’re not cut out for this, think again. Yes, there’re many fundamentals you have to master before you start building models, and yes, you’ll have to keep a steady learning pace as the community grows, but who said you have to do all that alone?
If you start your journey with a professional machine learning tutor, you’ll have an extra hand guiding you at every point. Superprof holds the authority on private lessons on advanced subjects, including AI and ML. They’ve got the perfect tutor to help you figure out where you stand in AI and how to take your journey smoothly and successfully. No matter which mathematic principle or programming language you want to start with, Superprof has got you covered.
How to Improve Skills in Machine Learning?
Getting started with this subject is only the first step. You’ll have to find new ways to improve your knowledge and skills to professional standards, which isn’t easy when the basics themselves take so much time and effort to get around.
You can try landing a job in the field of data science as it’ll give you the experience and preparation, but if that’s not an option for you, you can practice on your own. Build simple models and improve them from time to time. Applying your knowledge in real-world scenarios is crucial to becoming a prominent machine learning expert.
Other than practice, you can attend conferences and presentations about the growing potential of data science and AI. These events and exhibitions can prepare you for what’s to come and open your mind to the unimaginable possibilities of AI. We’ve mentioned the rapid growth of this industry, so without staying on top of it, you will be left behind.
Start Your AI Lessons with Superprof
That’s the verdict. AI and machine learning are demanding subjects, but they can be easy if you know what you’re doing. Understand what you want to do with this technology, figure out the key prerequisites that you need to learn, develop a deep understanding of the basic math and data science concepts, and then you’re ready to get started.
It’s a long journey, so if you ever get stuck at any point, remember that Superprof is here to help. We have a team of AI and machine learning tutors who belong to reputable machine learning institutions that will take you step by step through every chapter, so you can confidently stand as a data scientist and AI expert in the future. Explore the ins and outs of machine learning with Superprof today.
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