Hello, AI!
Hello.
This is my first post. The blog is intended mainly to keep track of my progress of learning Machine Learning, Deep Learning and Artificial Intelligence in general and to bring some interesting papers or discussion regarding abstract topics related to AI and/or consciousness, from different perspectives, even speculation of some sort.
As I've already gained some knowledge in the field, doing a few courses on Machine Learning, watching some YouTube videos and also read some books on this topic, I'm not actually starting from scratch.
But, this is my first post on this blog, so I thought maybe I should tell you and recommend what I've done and followed so far:
1. Andrew Ng's Coursera Machine Learning Course -> https://www.coursera.org/learn/machine-learning/home/welcome , which I strongly, not necessarily recommend it as starting point, as I felt really lost doing it and realised how much I don't know about the field. But it's good to get a good grasp of the concepts and also understand how Machine Learning works from scratch, as it's not using any of the well know and established Python/R libraries, as it's using Octave (a MatLab similar programming language/math software).
2. Trying to understand how Machine Learning works better, I've ran across this wonderfully written book, as it's easy to follow -> Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems. Perhaps the best book to start learning about Tensorflow, Google's Python library for Machine and Deep Learning project.
3. My first foray in the field was done through 3Blue1Brown's YouTube channel and especially his playlist on Neural Networks -> https://youtu.be/aircAruvnKk
The reason I highly recommend his channel is that he makes learning math fun and easy, and also his videos have very high quality content, animations and they're very easy to understand and follow.
4. A great book on understanding how the mind works and how it's possible to build robots/machines today is Ray Kurzweil's 'How to create a mind'. Very informative and interesting, I recommend this as a starting point to ML and AI, as it explains how the brain works and how we're possible to create AI today and tomorrow.
5 My last entry for this post is another speculative book, by Max Tegmark: 'Life 3.0'. It's a book that tries to explain and give reasons why AI is important, how we can develop it in an ethical and good way for humanity.
So, this is my first post in this journey of learning how to work with Machine Learning.
Next post I'll talk about some tools I'll use down the way (industry standard, almost) and also provide a brief explanation of what they do and why they're important.
This is my first post. The blog is intended mainly to keep track of my progress of learning Machine Learning, Deep Learning and Artificial Intelligence in general and to bring some interesting papers or discussion regarding abstract topics related to AI and/or consciousness, from different perspectives, even speculation of some sort.
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| A Venn diagram of AI, ML & DL |
As I've already gained some knowledge in the field, doing a few courses on Machine Learning, watching some YouTube videos and also read some books on this topic, I'm not actually starting from scratch.
But, this is my first post on this blog, so I thought maybe I should tell you and recommend what I've done and followed so far:
1. Andrew Ng's Coursera Machine Learning Course -> https://www.coursera.org/learn/machine-learning/home/welcome , which I strongly, not necessarily recommend it as starting point, as I felt really lost doing it and realised how much I don't know about the field. But it's good to get a good grasp of the concepts and also understand how Machine Learning works from scratch, as it's not using any of the well know and established Python/R libraries, as it's using Octave (a MatLab similar programming language/math software).
2. Trying to understand how Machine Learning works better, I've ran across this wonderfully written book, as it's easy to follow -> Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems. Perhaps the best book to start learning about Tensorflow, Google's Python library for Machine and Deep Learning project.
3. My first foray in the field was done through 3Blue1Brown's YouTube channel and especially his playlist on Neural Networks -> https://youtu.be/aircAruvnKk
The reason I highly recommend his channel is that he makes learning math fun and easy, and also his videos have very high quality content, animations and they're very easy to understand and follow.
4. A great book on understanding how the mind works and how it's possible to build robots/machines today is Ray Kurzweil's 'How to create a mind'. Very informative and interesting, I recommend this as a starting point to ML and AI, as it explains how the brain works and how we're possible to create AI today and tomorrow.
5 My last entry for this post is another speculative book, by Max Tegmark: 'Life 3.0'. It's a book that tries to explain and give reasons why AI is important, how we can develop it in an ethical and good way for humanity.
So, this is my first post in this journey of learning how to work with Machine Learning.
Next post I'll talk about some tools I'll use down the way (industry standard, almost) and also provide a brief explanation of what they do and why they're important.
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