Machine Learning for High Schoolers: How to Get Started With Machine Learning as a High Schooler
What is Machine Learning?
Machine learning is a specialized area within the realm of artificial intelligence and computer science that involves the utilization of data and algorithms to simulate human learning processes and enhance accuracy over time.
Recent advances in technological infrastructure, including increased processing power and storage capabilities, have paved the way for cutting-edge machine learning products such as Netflix's recommendation engine and autonomous vehicles.
In the field of data science, machine learning serves as a crucial tool for analyzing large datasets and generating valuable insights through the use of statistical methods and predictive algorithms. These insights drive decision-making processes in various industries and organizations, ultimately impacting growth metrics.
As the volume of big data continues to expand, there is a growing demand for data scientists who can help identify relevant business questions and the data necessary to answer them.
Frameworks such as TensorFlow and PyTorch are commonly used to create machine learning algorithms, allowing for the accelerated development of innovative solutions.
Why Machine Learning?
Why Does Machine Learning Matter?
Enterprises find machine learning to be a crucial tool as it allows them to gain insights into customer behavior and business operations, while also aiding in the creation of new products. The use of machine learning has become a key aspect of many of today's top companies, such as Facebook, Google, and Uber, as it contributes to their core operations.
Why Should High Schoolers Learn About Machine Learning?
Understanding ML concepts can boost students' confidence in tackling complex topics.
Developing an ML product provides diverse exposure to various roles in the technology industry.
ML is poised to become the next groundbreaking technology wave.
Studying ML enables you to comprehend its current limitations.
Proficiency in ML is crucial for envisioning the future of technology.
Mastering ML teaches you valuable skills in learning and adapting to new technologies.
Learning ML involves practical coding skills development.
Probability and statistics are indispensable tools for navigating life.
Discovering the usefulness of various school subjects is one of the benefits of learning ML.
By creating a functional product that meets people's needs, you can make a tangible impact.
Step by Step process for high schoolers to learn machine learning
1. Learning Python:
I would suggest learning Python as it is easy to learn and has many useful libraries for Machine Learning. I recommend Numpy, Pandas, and Matplotlib for data manipulation and visualization. For those who have no prior coding experience, the University of Toronto offers a free course that teaches the basics of Python. If you already have coding experience in a different language, just skim through a Python syntax tutorial.
2. Basics of Machine Learning:
To get started in Machine Learning, I highly recommend Andrew Ng's course, which is universally regarded as an excellent resource. It covers the basics of Machine Learning, although some concepts may be challenging for high school students. Taking notes during the course is helpful, but doing the programming-related exercises and tutorials in Matlab is not necessary.
3. Learning Machine Learning Algorithms:
To learn Machine Learning algorithms, I suggest taking Kirill Eremenko and Hadelin de Ponteves' course on Udemy, which covers both Python and R. They are experts in finding relevant ways to apply simple algorithms in real-life scenarios. If you're unwilling to pay for the course, you can also try Google's free Deep Learning course or the University of Michigan's free course, although they may not be as comprehensive as the paid course.
4. Independent Projects:
Lastly, I recommend practicing on simple datasets on websites such as Kaggle or the UCI Machine Learning repository. Some easy datasets to start with are the Iris, Wine, Breast Cancer Wisconsin, Autism Screening, Congress Voting, Handwritten Digits MNIST, and Fashion MNIST datasets. Try experimenting with different algorithms and optimizing performance.
Best High School Program to Start Your Machine Learning Journey
Artificial Intelligence Summer 2023 Program by Stanford Alumni
Inspirit AI inspires curious high school students globally by exposing them to the defining technology of our times: Artificial Intelligence. AI is already present everywhere: in our voice-activated devices, smartphone face recognition systems, and autonomous vehicles. The potential to apply this technology for good is limitless.
This program — developed and taught exclusively by a team of alumni and graduate students from Stanford, MIT, and other top universities — provides guidance on initiating AI projects, pursuing AI ventures, and preparing for college. Learn more about our live online program.
Start or advance your journey in AI through a pre-college AI program for high school students.
Learn from Stanford alumni and graduate students specializing in AI, who work with students in small groups.
Collaborate with a mentor on a socially impactful AI project and receive guidance on pursuing AI careers and ventures.
Prepare for college applications through experiential workshops from Stanford and MIT students and alumni.
Advanced Machine Learning Projects for High Schoolers
Recommender System Projects
Sales Forecasting Project
Stock Price Prediction Project
Build a Sorting, Categorizing, and Tagging System
Patient's Sickness Prediction System
AI-driven Sentiment Analyzer
Email Spam-Filtering System
Digit Classification Project using MNIST Dataset
Credit Card Fraud Detection Project
Fake News Detection Project
Sign language Recognizer
Speech Emotion Recognizer
Music Genre Classification System
Intelligent Chatbots
Image Caption Generator
Boosting Your High School Resume
One of the trendiest careers in the twenty-first century is machine learning. Hands-on experience on a variety of projects prepares you like nothing else for real-world problem-solving. A machine learning project will help you boost your college application. In addition to your technical abilities, you must market yourself through your model’s effectiveness. Here are some key factors related to the ML project that you must highlight in order to develop an amazing high school portfolio.
Make an effort to state your ML project's name as clearly as feasible. The name itself will describe the key characteristics that the organization seeks in recruits.
Under the project header, provide all pertinent project names.
You must follow a suitable sequence order (let's say, chronologically). Place the most recent projects first, followed by previous projects.
Each project title should provide a summary of the project, highlighting the libraries, frameworks, and datasets that were used.
Remember to include any tools, programs, APIs, or software that you utilized while building your project. Also, if you are a member of any community (such as Kaggle or another Git project), include their names.
Link to your own website, blog, or GitHub repository where you have uploaded your project in your CV. It will provide recruiters with a thorough understanding of your project.
About Inspirit AI
AI Scholars Live Online is a 10 session (25-hour) program that exposes high school students to fundamental AI concepts and guides them to build a socially impactful project. Taught by our team of graduate students from Stanford, MIT, and more, students receive a personalized learning experience in small groups with a student-teacher ratio of 5:1.
