• Book Name: Machine Learning for Absolute Beginners by Oliver Theobald
  • Author: Oliver Theobald
  • Pages: 128
  • Size: 3 MB

Machine Learning for Absolute Beginners Pdf Free Download

Machines have come a long way since the Industrial Revolution. They continue to fill factory floors and manufacturing plants, but now their capabilities extend beyond manual activities to cognitive tasks that, until recently, only humans were capable of performing. Judging song competitions, driving automobiles, and mopping the floor with professional chess players are three examples of the specific complex tasks machines are now capable of simulating.

But their remarkable feats trigger fear among some observers. Part of this fear nestles on the neck of survivalist insecurities, where it provokes the deep-seated question of what if? What if intelligent machines turn on us in a struggle of the fittest? What if intelligent machines produce offspring with capabilities that humans never intended to impart to machines? What if the legend of the singularity is true?

The other notable fear is the threat to job security, and if you’re a truck driver or an accountant, there is a valid reason to be worried. According to the British Broadcasting Company’s (BBC) interactive online resource Will a robot take my job?, professions such as bar worker (77%), waiter (90%), chartered accountant (95%), receptionist (96%), and taxi driver (57%) each have a high chance of becoming automated by the year 2035.
But research on planned job automation and crystal ball gazing with respect to the future evolution of machines and artificial intelligence (AI) should be read with a pinch of skepticism. AI technology is moving fast, but broad adoption is still an unchartered path fraught with known and unforeseen challenges. Delays and other obstacles are inevitable.

Nor is machine learning a simple case of flicking a switch and asking the machine to predict the outcome of the Super Bowl and serve you a delicious martini. Machine learning is far from what you would call an out-of-the-box solution.

Machine Learning for Absolute Beginners Pdf Free Download

Machines operate based on statistical algorithms managed and overseen by skilled individuals—known as data scientists and machine learning engineers. This is one labor market where job opportunities are destined for growth but where, currently, supply is struggling to meet demand. Industry experts lament that one of the biggest obstacles delaying the progress of AI is the inadequate supply of professionals with the necessary expertise and training. According to Charles Green, the Director of Thought Leadership at Belatrix Software: “It’s a huge challenge to find data scientists, people with machine learning experience, or people with the skills to analyze and use the data, as well as those who can create the algorithms required for machine learning. Secondly, while the technology is still emerging, there are many ongoing developments. It’s clear that AI is a long way from how we might imagine it.” 

Perhaps your own path to becoming an expert in the field of machine learning starts here, or maybe a baseline understanding is sufficient to satisfy your curiosity for now. In any case, let’s proceed with the assumption that you are receptive to the idea of training to become a successful data scientist or machine learning engineer.

To build and program intelligent machines, you must first understand classical statistics. Algorithms derived from classical statistics contribute the metaphorical blood cells and oxygen that power machine learning. Layer upon layer of linear regression, k-nearest neighbors, and random forests surge through the machine and drive their cognitive abilities. Classical statistics is at the heart of machine learning and many of these algorithms are based on the same statistical equations you studied in high school. Indeed, statistical algorithms were conducted on paper well before machines ever took on the title of artificial intelligence.

Computer programming is another indispensable part of machine learning. There isn’t a click-and-drag or Web 2.0 solution to perform advanced machine learning in the way one can conveniently build a website nowadays with WordPress or Strikingly. Programming skills are therefore vital to manage data and design statistical models that run on machines. Some students of machine learning will have years of programming experience but haven’t touched classical statistics since high school. Others, perhaps, never even attempted statistics in their high school years. But not to worry, many of the machine learning algorithms we discuss in this book have working implementations in your programming language of choice; no equation writing necessary. You can use code to execute the actual number crunching for you.

If you have not learned to code before, you will need to if you wish to make further progress in this field. But for the purpose of this compact starter’s course, the curriculum can be completed without any background in computer programming. This book focuses on the high-level fundamentals of machine learning as well as the mathematical and statistical underpinnings of designing machine learning models.

For those who do wish to look at the programming aspect of machine learning, Chapter 13 walks you through the entire process of setting up a supervised learning model using the popular programming language Python.

Machine learning for absolute beginners pdf free download.


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