Published in Towards Data Science·2 days agoMember-only25 Numpy Treasures Buried in the Docs Waiting to Be FoundGet rich in NumPy — Motivation Every data scientist admires someone. For some, it might be people who create killer data visualizations; for others, it is simply anyone who answers their StackOverflow questions. For me, it was people who used NumPy like a ninja. I don't know. I have always thought that the ability to use…Machine Learning9 min read
6 days agoMember-only28 Subtle Weekly Machine Learning Tricks And Gem Resources, #5August 8–14 issue — Welcome to the fourth edition of my newsletter — Tricking Data Science. This issue contains another 28 of my LinkedIn posts for the past week. Thanks to everyone for reading the latest issues! Here are links to them👇 28 Subtle Weekly Machine Learning Tricks And Gem Resources, #4 July 24–31 issueibexorigin.medium.com 28 Subtle Weekly Machine Learning Tricks and Gem Resources, #3 July 10–16 issueibexorigin.medium.comArtificial Intelligence13 min read
Published in Towards Data Science·Aug 4Member-only20 Python Gem Libraries Buried In the Installation Waiting To Be FoundGet to know Python's standard libraries like never before — Introduction Most people think Python's mass dominance is due to its powerful packages like NumPy, Pandas, Sklearn, XGBoost, etc. These are third-party packages written by professional developers, often with the help of other faster programming languages like C, Java, or C++. So, one of the feeble arguments haters might throw against…Artificial Intelligence8 min read
Jul 31Member-only28 Subtle Weekly Machine Learning Tricks And Gem Resources, #4July 24–31 issue — Welcome to the fourth edition of my newsletter — Tricking Data Science. This issue contains another 28 of my LinkedIn posts for the past week. Thanks to everyone for reading the latest issue and for such positive feedback. Here are the past issues: 28 Weekly Machine Learning Tricks And Resources That Are Pure Gems #1 Learn machine learning one snippet at a timeibexorigin.medium.comArtificial Intelligence15 min read
Published in Towards Data Science·Jul 27Member-onlyComprehensive Tutorial on Using Confusion Matrix in ClassificationLearn to control model output based on what's important to the problem using a confusion matrix — Master the fundamentals of the confusion matrix using Sklearn and build a practical intuition for three of the most common metrics used in binary classification: precision, recall, and F1 score. Introduction Classification is a massive part of machine learning. Its benefits and applications are endless — ranging from detecting new asteroids…Data Science12 min read
Published in Towards Data Science·Jul 22Member-onlyOne-Stop Tutorial on All Cross-Validation Techniques You Can (and Should) UseAll CV procedures you need to know as a data scientist, explained — Why cross-validate? Until I start selling the related merchandise, I gotta advertise the main idea. Here it goes. Let’s imagine a world where you don’t know what a cross-valıdatıon procedure is. In that crazy world, you obviously split your data into a single train and test sets. The model learns from the…Machine Learning8 min read
Jul 13Member-only28 Subtle Weekly Machine Learning Tricks and Gem Resources, #3July 10–16 issue — Welcome to the third edition of my newsletter — Tricking Data Science. This issue contains another 28 of my LinkedIn posts for this week (both published and unpublished). Thanks to everyone for reading the latest issue and for such positive feedback. 26 Weekly ML Tricks And Resources That Are Pure Gems, #2 July 3–9 issueibexorigin.medium.com 28 Weekly Machine Learning Tricks And Resources That Are Pure Gems #1 Learn machine learning one snippet at a timeibexorigin.medium.comArtificial Intelligence12 min read
Published in Towards Data Science·Jul 12Member-onlyAdvanced Tutorial: How to Master Matplotlib Like an Absolute BossUse Matplotlib like never before — I used to have a rule… When I was a beginner learning data visualization, I used to have a rule — never, ever visit the Matplotlib documentation. Nothing good ever came out of there. When I was on its pages, my eyes would process English words but, somehow, they were interpreted into my brain like I…Data Science9 min read
Jul 6Member-only26 Weekly ML Tricks And Resources That Are Pure Gems, #2July 3–9 issue — Introduction Welcome to the second edition of my newsletter — Tricking Data science. This issue contains another 26 of my LinkedIn posts for this week (both published and unpublished). It also contains a post that went pretty viral — over 120k views. Guess which post it is! Here is the last…Artificial Intelligence10 min read
Published in Towards Data Science·Jul 5Member-only10 Sklearn Gems Buried In the Docs Waiting To Be FoundHidden treasures — Motivation I hated Sklearn. The “first introduction to ML” course I took explained SVMs so badly that I judged the entire library based on that. I abandoned the course and ML for good for a few months after that. Little did I know that Sklearn would turn out to be my…Artificial Intelligence9 min read
