Python for Machine Learning Video Tutorials

Python is an open-source, general-purpose programming language that can be used for machine learning. Machine learning is a type of artificial intelligence that leverages data to automate tasks. Watching video tutorials online is a popular method of learning Python for machine learning. Videos work well for auditory and visual learners, can be paused and replayed as often as you like, and can easily be bookmarked to return to later. Videos also allow you to learn at your own pace. This article will cover tips for learning with videos.

What is Python for Machine Learning?

Python is an open-source, general-purpose programming language first developed in 1991. Because Python is open-source, it is free and publicly available for anyone to use. Python can be used to build websites, develop software, conduct data analysis, and automate tasks using artificial intelligence (AI) and machine learning. 

Machine learning enables computer systems to automatically learn and adapt without manual input. The system does this by using statistical models and algorithms to detect patterns in data. Python’s libraries and frameworks, along with the coding language’s platform independence, popularity and community, concise and readable code, flexibility, and consistency, make it a perfect fit for machine learning. 

Read more about what Python is and why you should learn it for machine learning.

What Can You Do with Python for Machine Learning?

Python is a general-purpose programming language that you can use to create data visualizations, write programs for machine learning, analyze data, make file directories, build apps, and more. Because of its many applications in using and managing data, Data Scientists must have a thorough knowledge of Python programming and its uses. 

Python for machine learning is used to personalize and improve user experiences. Machine learning can automate customer support, detect fraudulent transactions, recommend products, refine search engine results, automate translation, recommend music, and predict the effectiveness of drug treatments. There are countless uses for machine learning and demand is only increasing, making now an opportune time to learn Python for machine learning.

Why Are Video Tutorials Helpful When Learning Python for Machine Learning?

Videos can help you learn new skills thanks to the way they appeal to different types of learners. Videos contain visual and audible elements for those who learn best by seeing and hearing. You can even get some hands-on experience by following along with video tutorials or completing video exercises that may accompany a video course. This section discusses these benefits in more detail below.

Video Tutorials for Visual Learners

Video tutorials are a great way for visual learners to practice their Python for machine learning skills. Video tutorials visually demonstrate how to perform Python for machine learning tasks and often contain other visual elements such as graphs and charts. Visual learners can also pause and replay the video to take in the different visual elements and commit them to memory. You can watch videos on a mobile device or on a desktop computer. If you intend to follow along with the video, you will want to view it on a desktop computer so that you have access to the coding tools needed for the exercise. Watching on a larger screen makes it easier to take in the video’s visual elements. If there are particular visuals within the video that you want to reference later, you can see if the video contains a download link for the visuals, or you can take a screenshot and save it to your computer.

Video Tutorials for Auditory Learners

Videos have audio content that you can listen to repeatedly, which is especially helpful for those who learn best by hearing. You don’t have to be an auditory learner to benefit from audio content as many people benefit from a mixed approach to learning. You can pause and replay videos, save videos to listen to again later, and commit the video contents to memory. Mobile apps make it easy to listen to video lessons wherever you are, though if you intend to code along with a video tutorial, you will need to use a desktop computer.

Video Tutorials for Kinesthetic Learners

Kinesthetic learners, also known as tactile learners, learn best by doing. Hands-on activities help kinesthetic learners commit new skills to memory, but even those who are not tactile learners will benefit from hands-on activities. Every learner requires first-hand experience to truly master programming skills. The best way to gain hands-on experience with video learning is to follow along with video tutorials. You can pause and replay videos as needed as you work through tutorials and exercises step by step. You will need to do these activities on a desktop computer and want to ensure you have the proper tools installed.

Learn on Your Own Schedule 

Most video classes are also on-demand or self-paced classes, meaning that you proceed at your own pace and set your own schedule. This offers a lot of flexibility as to when and how much you learn. The biggest challenge with such a class is the self-discipline needed to learn consistently. Therefore, it helps to set a time every day or throughout the week to learn so that you make learning a part of your routine and stay on track with your course. Although most on-demand classes do not have scheduled meeting times, they may include deadlines for certain assignments. You will want to keep track of those due dates to ensure your assignments are submitted on time. 

Types of Python for Machine Learning Videos

This section offers details on free and paid video options for learning Python. 

Free Python for Machine Learning Videos 

You can start learning Python for machine learning at no cost through the use of free videos. Free resources typically provide a high-level overview rather than a detailed explanation of Python for machine learning, but can provide an excellent starting place. If you do not have previous experience with Python programming, you will need to master Python fundamentals before learning Python for machine learning. Noble Desktop’s Intro to Python Fundamentals video course covers crucial information regarding the Python programming language and the many ways you can use Python in data science and data analytics. 

You can also find free introductory Python courses from Google, Microsoft, and on learning platforms like Udemy and Coursera.

Paid Python for Machine Learning Videos

You can find paid Python programming classes through subscription learning platforms. These platforms include LinkedIn Learning, Udemy, and Coursera. These paid subscriptions typically cost between $30 and $60 per month. As it can take multiple months to complete certain courses, you will want to remember the recommended schedule when budgeting for these video classes. While most video courses, also known as on-demand courses, proceed at your own pace and schedule, some classes may include deadlines for assignments, in which case you will want to keep track of those due dates so that you don’t fall behind. Some classes also include an instructor you can contact via email if you have questions, though it may take a few hours or days to get a response.

Why Learn Python for Machine Learning?

Machine learning is an increasingly important component in personalizing and improving user experience and automating tasks. Machine learning algorithms are used to make product recommendations to shoppers on Amazon, manage trading on Wall Street, and choose what plans next in your Spotify playlist. 

Learning Python for machine learning can advance your current career or help you start a new one. Employers look for this highly desirable skill when hiring Data Analysts and Data Scientists, so learning Python for machine learning can help your resume stand out. If you learn Python for machine learning through an instructor-led course with hands-on projects, you can add those projects to your professional portfolio to showcase your abilities to potential employers.

How Difficult is It to Learn Python for Machine Learning?

Before learning Python for machine learning, you must demonstrate a solid understanding of Python programming and the NumPy and Pandas libraries. While many consider Python a relatively easy coding language for experienced programmers to learn, it can prove challenging, especially for students new to coding. If you do not have a background in data science, learning Python and machine learning as part of a data science certificate program can help you build data science skills, starting with the fundamentals, then building your way up to topics like machine learning. 

The Python programming language is an open-source coding language, meaning that anyone can download it for free. You can find the latest version of Python, view documentation, join the Python community, and more through the Python Software Foundation’s website. 

Read about how difficult it is to learn Python for machine learning.

Learn Python for Machine Learning with Hands-on Training at Noble Desktop

Noble Desktop offers instructor-led courses that provide hands-on experience using Python for machine learning. You can take a specialized course such as the Python for Machine Learning course or learn this skill through the Data Science Certificate program. 

The Python for Machine Learning course requires students to have a strong foundation in Python programming and its data science libraries NumPy and Pandas prior to enrollment. If you do not have previous experience with Python programming, you can satisfy this prerequisite by first taking Noble’s Python for Data Science Bootcamp.

If you want to learn Python for machine learning as part of a broader curriculum, especially if you want to launch a new career in data science, the Data Science Certificate program covers essential skills in a single program. This program includes small classes, 1-on-1 mentoring, setup assistance, a free retake, flexible payment options, hands-on experience, and job search assistance.

Explore live online Python for machine learning classes that connect you to expert instructors for real-time feedback and guidance.