Sometime back, I wrote about why I have started mentoring and the scope of fields in which I am interested in mentoring. Not long ago, I broadened my horizon further to include Machine Learning in the scope. Hence, I have prepared a Machine Learning Roadmap which is quite hands-on, will nudge you to pursue your curiosity and, is supposedly less boring and more intriguing – which reduces the overall probability of dropping off in comparison to video lecture courses out there. The roadmap is designed for you to learn Machine Learning in a step-wise manner. It would equip you to learn and gain hands-on experience in streams like data cleaning, data visualization, exploratory data analysis, data modeling, etc.
In the blog, I will give you a walkthrough of the Machine Learning Roadmap, how to download it and would encourage you to write or talk to me if you need help. In the end, you can give me a feedback on how did the Machine Learning Roadmap helped you, and how can it be further improved!
Machine Learning Roadmap Walkthrough
The roadmap has several key components: Tracks, Milestones, Activities, Timeline, Status and Comments.
Track, as the name suggests, represents a theme. Within each individual tracks, there are key milestones which would represent that you have completed the track.
Subsequently, you will find a list of activities within each track. This list of activities is, obviously, not exhaustive. It’s designed in a way that will make you think and explore more about why you are doing – what you are doing. In general, that’s the key to learning anything new as well! Besides activities, there are timelines and comments section. The timelines are for you to indicate how much time you would want to dedicate or in how much time you completed the track.
Then there is a status section in which you can highlight whether a track has been completed, or if it’s still in progress. The comments section is for you to highlight something specific for your own reference or for further clarification.
I can’t stress this enough but I still wish to re-iterate, follow your curiosity while doing the activities! If you are completely new to machine learning and you come across an activity which asks you to import a dataset using Pandas – please go and read about what’s Pandas, why are we using Pandas. That will help you to have a better grip over the tracks and activities.
Another note: I have intentionally kept timeline empty because I don’t know your current work or academic pressure. Hence, I can’t assign a set date to any activity. However, I have seen a lot of people perform better in scenarios wherein they are given deadlines. So just as a yardstick, you can target to complete each track in 1 week or less.
Download the Machine Learning Roadmap
You can download the roadmap from the link below.
It’s completely okay to ask for help. If you are stuck at some activity, want to know more about why a technique is applied, or if the machine learning roadmap is just not working out and you would prefer a little more handholding – these are all legit things to call out for help! If that’s the case, feel free to drop me a mail or message (just so that I am prepared to answer your query) and schedule a call.
Future Steps and Feedback
I have a few things planned for the Machine Learning Roadmap v2.0 including adding a plug-and-play jupyter notebook and asking you to optimize certain pieces of code, and many more!
Since this roadmap is completely free, I would really appreciate every bit of constructive feedback. I would also feel great to know how this Machine Learning Roadmap helps you. But wait! If you really insist, you can buy me a coffee if you are in Singapore or if you prefer to do it virtually, then
Feel free to reach out! My contact details are here.