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Sanskar

Keen Learner and Exp... • 10h

Day 8 of learning Data Science as a beginner topic: multidimensional indexing and axis NumPy also allows you to perform indexing in multidimensional arrays i.e. in simple terms numpy allows you to access and manipulate elements even in arrays containing more than one dimensions and that's exactly where the concepts of axis comes in. Remember we used to plot points on graphs in mathematics and there were two axis(x and y) where x was horizontal and y vertical in the same(not exactly same though) way in numpy we refer to these as axis 0 and axis 1. Axis 0 refers to all the rows in the array and all the operations are performed vertically i.e. suppose if you want to add all the rows then first the 0th index of all rows gets added(vertically of course) followed by the successive indices and axis 1 refers to the columns and its operations are performed normally. Cutting it short and simple you may suppose axis 0 as y axis and axis 1 as x axis on a graph. These axis and multidimensional indexing have various real life applications as well like in data science, stock analysis, student marks analysis etc. I have also tried my hands on solving a real life problem related to analyzing marks of students. Also here's my code and its result along with some basics of multidimensional indexing and axis.

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Sanskar

Keen Learner and Exp... • 7d

Day 6 of learning Data Science as a beginner. Topic: creating NumPy arrays NumPy arrays can be created using various ways one of them is using python list and converting it into a numpy array however this is a long way here you first create a pytho

Sanskar

Keen Learner and Exp... • 5d

Day 7 of learning Data Science as a beginner. Topic: Indexing and Slicing NumPy arrays Since a past few days I have been learning about NumPy arrays I have learned about creating arrays from list and using other numpy functions today I learned abou

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Day 12 of learning AI/ML as a beginner. Topic: TF-IDF practical. Yesterday I shared my theory notes and today I have done the practical of TF-IDF. For the practical I reused my spam classifier code and for TF-IDF I first imported it from the sklear

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Sanskar

Keen Learner and Exp... • 8d

Day 5 of learning Data Science as a beginner Topic: Using NumPy in Data Science Python despite having much advantages (like being beginner friendly, easy to read) is also famous for its one limitation i.e. it is slow. We don't really feel much abou

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Learned OOPS concepts took me 3 days to wrap it up! Next up: diving into NumPy. Step by step, building a strong foundation for my AIML journey. Anyone else on the same path or wanna join in? Let’s learn and grow together! 🚀 #Python #OOPS #NumPy #AIM

Sanskar

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Day 2 of learning mathematics for AI/ML as a no math person. Topic: vectors and matrices. We use NumPy python library for these. I got introduced to the concept of vectors and matrices. Vectors are like lists and are divided Vectors are divided in