Also, my fan letter for David and his book
Forget that hip new technology! To take your Data Science/Analysis career to the next level, learn... how to write well.
How being a good writer can take your career to the next level
Forget that hip new technology! To take your software development career to the next level, learn... how to write well.
Tough questions to ask your remote employer who gives you Cost Of Living based compensation and some thoughts on how remote compensation will work in the future
Simple rules for better programming that are generally neglected by newcomers
20 cool project ideas for data science, machine-learning app development, and web development
A guided project that helps you dive into creating something cool and learn useful programming concepts by yourself!
3 systems to make self-learning easier, Mentors to follow on Twitter and Cool Project Ideas for learning
What I will do is I sew a very simple explanation of Gradient Boosting Machines around the parameters of 2 of its most popular implementations — LightGBM and XGBoost.
What I also want to say is that these cool webpages/people that I come across can come to anyone.
I analysed the Stack Overflow survey and found a stark contrast in salaries, youth, interest in new tools, opinions about AI, ethics and more..
Earlier, I wasn’t so sure. I would say something like do this course or read this tutorial or learn Python first (just the things that I did). But now, as I am going deeper and deeper into the field, I am beginning to realise the drawbacks of the approach that I took.
With hundreds of papers being published every month, anybody who is serious about learning in this field cannot rely merely on tutorial-style articles or courses where someone else breaks down the latest research for him/her.
“Every great developer you know got there by solving problems they were unqualified to solve until they actually did it.”
It almost eases the mind to believe that we have this intangible sort of.. man-made “thing” that is analogous to the mind itself! It is especially appealing to someone who has just begun his/her Deep Learning journey.
A good problem provides a stage. A stage where you can apply your knowledge, see its effects, and draw conclusions from it to improve and go back to perform.
For a long time, I relied solely on my formal education. I put too much faith in it. Last year, when I joined college and all that faith fell off a cliff, I