What does the future of humanity look like? Machine learning and artificial intelligence are pushing all kinds of business, innovation, research and other areas to a whole new level, especially in developed countries. The time has come for Nepal to embrace the power of machine learning and artificial intelligence to tackle the difficult problems that the country has faced for centuries. Natural disasters, precision agriculture, managing road traffic, environmental sustainability are the perfect candidates for the next technological revolutions.
As a middle school student in America, I have had the privilege of learning programming and machine learning along with theoretical foundations from experts in the field. I invite the girls of Nepal to join me in learning the foundations of data science and machine learning so that we not only help the country to grow with a future army of machine learning experts, but also smooth out the wrinkles of the gender gap in Nepal. It is obvious that one of the most significant steps toward breaking the gender barrier is through empowering girls. Let's make it happen!
Your future is powered by code; if you want to build for the future, you'll need to learn how to code. Here, I propose an innovative idea about the most sophisticated tool that is transforming the world right now. I invite the girls of Nepal to join me in learning how to code for predictive analytics and machine learning. My purpose for this call is twofold: first, to contribute to reducing the gender gap, and second, to have fun teaching coding and machine learning.
Coding, or computer programming, is a vital tool in science, engineering, business and many other fields that will help you tremendously in achieving your goals. Coding is the language of machine learning and predictive analytics. The developed countries of the world are undergoing a major transformation in their economies thanks to the very powerful algorithms of machine learning and artificial intelligence (AI). But how does it work?
Machine learning is a futuristic idea that has been in the making for quite some time now. It is a set of algorithms that predicts patterns and data on a large scale. Machines are learning how to process vast amounts of data in order to improve our lives in ways we can't even fathom. Machine learning is a set of computer algorithms that learn how to make predictions based on the information provided. With human intelligence, it is difficult to make predictions with datasets that are too large, complex, or vast. In contrast, machines will be able to take the data and make the predictions that humans cannot.
Take an example of AlphaGo with which began the global sensation of AI. Designed in 2015, AlphaGo, an AI with unimaginable power, won against the best of the best in the game of Go. The best part is, the designer of AlphaGo has no clue how to play the game.
Whereas AlphaGo is an example of a full-blown powerful AI, what I am proposing here is the route to becoming a specialist in various types of predictive analytics and machine learning. Conventionally, AI has been treated as a broad spectrum of techniques that solve a computational task. This can theoretically include many techniques, many of them being not-so-great historically. Machine learning is a suite of powerful statistical models and algorithms that have developed dramatically in these last few decades. These days, when the media talks about AI, they usually refer to a specific version of the ML models called deep learning or its variants.
Machine learning is a remarkable set of technologies that can be used for a wide variety of applications. One of the algorithms I’ve written is 97% accurate in detecting breast cancer. For this, I used a database of over 11,000 medical records published online. The model I wrote learns to distinguish a case of breast cancer from a healthy breast by comparing many characteristics of breasts afflicted with cancer versus the ones without. Machine learning is the foundation of the future of healthcare. Experts believe that half of the medical discoveries and innovations will come from machine learning in a decade, as opposed to the current heavy reliance on hard-core scientific research as of now.
Machine learning algorithms are used for many kinds of applications such as in healthcare, email filtering, speech recognition, computer vision, search engine queries, and many more. The question is, can we create an army of ML experts in Nepal and make a dent in the gender gap with the proper training and mindset?
Machine learning, specifically AI driven by the architecture of deep learning model, is transforming the industries of the developed world. Whereas all these achievements sound far-fetched, especially in a developing country like Nepal, they were all achieved with the application of powerful algorithms. For that, all you need is a passion to learn how to code and to learn the theory. I am myself learning machine learning, and have already been able to use some of the machine learning models I have programmed in various predictions. It gives me pleasure when I can teach what I have learnt and help reduce the gender gap at the same time. If you are curious about coding, data engineering and machine learning, join me online in gaining this new knowledge.
In this programming and machine learning course, I will walk you through the basics of programming. This foundational material about scripting is the first step in programming of any type of analytics. And this is going to enrich you with a whole new suite of scripts to perform many essential tasks in analytics. The skills in foundational programming will also come handy when you want to solve many kinds of real-world problems. For example, I like to program and solve problems that come up in college-level probability courses. I am able to do this via programming even when I don’t understand the math.
I have created a few articles showing several of these problems, their code, and solutions. For example, roll several dice at the same time and if you observe the same number in more than one dice repeatedly, those outcomes can be simulated with the code I published here. In another article here, I show how the chances of two students in a group of 25 having the birthday on the same day are actually pretty high. I have also published my code here to find the probabilities of various kinds of card games. In addition, I simulated the famed Monty Hall Problem to solve the puzzling question as to which choice would help you win the game. The simulation of the situation [available at my GitHub] revealed that the answer was not what I had thought.
Whereas you can do many types of problem-solving with the basics of programming like I showed above, the main goal of this first course is to get ready for machine learning. Once the basics of programming are completed, I will walk you through several models of machine learning. If you are interested, sign up today for this free course. All you need is a computer, and the desire to learn!
Registration form: [Link]
(Roselyn Mainali is a middleschooler in Maryland, USA. She loves playing the piano, binge watches Cosmos and other science videos, is currently working on machine learning algorithms, and, occasionally, solves college-level math problems using simulation in R and publishes them to medium.com and GitHub.)
