Machine learning scholar adventure: Chapter 4

What progress did I make? Machine learning Deep Learning for Coders with Fastai and Pytorch: AI Applications Without a PhD The fastai book is still my main focus since my last progress update on MLSA: Chapter 3. Chapter 3: Data ethics I gained further insight into the ethical implications of AI technology. This was my first time where I realised that just like any other technology, data based creations are just as likely to be misused in the same way as other technological developments. Humans make technology generally to improve life but there is no guarantee that something which is… Continue reading

Machine learning scholar adventure: Chapter 3

What progress did I make? Machine learning Deep Learning for Coders with Fastai and Pytorch: AI Applications Without a PhD The fastai book has been my main focus since my last progress update on MLSA: Chapter 2. I have also been supplementing working through the book with viewing the related online course videos. I really like the fastai book because the approach is based on top down learning where the emphasis is on using deep learning as soon as possible. This was really powerful because the field’s myths were demystified rapidly, I got to see the capability of models available… Continue reading

Machine learning scholar adventure: Chapter 2

What progress did I make? Hell yeeeeaaah ? I’ve made strong positive progress with my MLSA and I am super happy! I can finally feel the strength of the momentum I’ve been aspiring for.  I’ve gotten better with prioritising my learning, maintaining consistency and keeping myself enthused. Without further ado, here’s what I’ve been up to: Machine learning Kaggle learn: Pandas This was a great introduction to the capabilities of the pandas library. Whilst I knew very basic pandas e.g. selecting rows, columns etc, I was less knowledgable about intermediate concepts. Now, I’m more comfortable with maps, understand grouping and… Continue reading

Review: Make your first GAN with Pytorch

Please note: As an Amazon Associate I earn from qualifying purchases. Summary The first time I learned that computers could create novel media was when I randomly found out about fractals. What were these strange shapes? I was amazed and quickly got a fractal wallpaper but didn’t explore much further. However, during this year, I became aware of content generation using machine learning! For example, researchers were able to generate human faces that didn’t even exist ? I was astounded. What was this GAN they kept mentioning? How did they work? Even I couldn’t tell the difference between the fake… Continue reading

Machine learning scholar adventure: Hiatus

What a year! As you may have noticed, I’ve been quiet on updating progress with my MLSA (machine learning scholar adventure). You may be wondering why? Well, unless you’ve been living under a rock…the world has been suffering from the effects of covid-19 for most of this year. Whilst I’m fortunate enough not to have been infected (unless I’m asymtomatic), it did affect other areas of my life negatively. During that time, I was busy putting out multiple fires and focusing on staying sane by looking after my physical, mental and emotional health. I’m glad that I survived with everything… Continue reading

Machine learning scholar adventure: Chapter 1

What progress did I make? Wow, can’t believe how quickly time has flown by. With regards to my MLSA, there has been both positive developments and negative occurrences, I’ve learned how to be better from both. One of the major things I’ve realised is how critical it is that I approach this endeavour with maximum integrity! Part of this means being really genuine and honest with the struggles I’ve been facing so that if others ever feel like giving up or they can’t make it or they aren’t good enough to be in this field, they can look at my… Continue reading

The machine learning scholar adventure

What is the adventure? The machine learning scholar adventure (MLSA) is a self-directed learning journey designed to ramp up my knowledge in machine learning rapidly ? It’s inspired by the structure of the OpenAI’s Scholars program, which works by providing a stipend for 4 months for full time study, pairing you with a mentor and also giving cloud credits for machine learning experiments! Even though, I’m not able to pursue it (e.g. one limitation is that only those in the US can apply), I believe that the most important aspects can be replicated! Consequently, I will follow a curriculum, blog regularly (at… Continue reading

Setting up the Kaggle API on your Paperspace machine

Hello there ?? Welcome to the way of the machine ? What is Kaggle? It’s an incredible platform that lets you practice your machine learning skills via competitions ? Although I’m just getting started, it’s highly regarded as one of the best ways to accelerate your skills in the machine learning community ?? Where does Paperspace come into this? For those without their own heavy-duty hardware, Paperspace allows you to rent the computing power you need for machine learning ? It’s the ideal way for students taking the fast.ai courses to set up a machine learning environment. This guide shows… Continue reading