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Sanskar

Keen Learner and Exp... • 1d

Day 9 of learning Data Science as a beginner. Topic: Data Types & Broadcasting NumPy offers various data types for a variety of things for example if you want to store numerical data it will be stored in int32 or int64 (depending on your system's architecture) and if your numerical data has decimals then it will be stored as float32 or float64. It also supports complex numbers with the data types complex128 and complex64 Although numpy is used mainly for numerical computations however it is not limited for numerical datatypes it also offers data types for sting like U10 and object data types for other types of data using these however is not recommended and is not where pythonic because here we are not only compromising with the performance but we are also destroying the very essence of numpy as its name suggests it is used for numerical python Now lets talk about Vectorizing and Broadcasting: Vectorizing: vectorizing means you can perform operations on an entire arrays at once and do not require to use multiple loops which will slow your code Broadcasting: Broadcasting on the other hand mean scaling of arrays without extra memory it “stretches” smaller arrays across larger arrays in a memory-efficient way, avoiding the overhead of creating multiple copies of data Also here's my code and it's result

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Sanskar

Keen Learner and Exp... • 9d

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

Yogesh Jamdade

..... • 1y

NumPy 2.0: A Game Changer (Released June 2024) NumPy 2.0, released in June 2024, is a major update for scientific computing in Python. Here's what's exciting: Variable-length strings: Finally! Store and manipulate text data with ease using new `Str

Sanskar

Keen Learner and Exp... • 10d

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

Kevin Patel

Learner 🍂🤎 • 1y

Some one please guide me for the road map of the data science: Skill I do have right now is Python, numpy , pandas (learning) After completing pandas, numpy and Excel can I do freelancing.. It will be so helpful if someone guides me

2 Replies

Comet

#freelancer • 10m

Essential Python Topics for Data Analysts 😄👇 - Data Structures: Lists, Dictionaries, Sets, and Tuples. - NumPy: Array manipulation for numerical operations. - Pandas: Data manipulation and analysis with DataFrame. - Data Cleaning: Handling missin

2 Replies

Sanskar

Keen Learner and Exp... • 7d

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

Harish Kumar

Training Consoler • 9m

Python is a beginner-friendly and powerful programming language, perfect for diving into data science. Start by learning the basics like variables, loops, and functions. Explore popular libraries such as Pandas for data manipulation, NumPy for nume

Medina Jalal

EComm Marketing Stra... • 6m

We Indian contribute to 20% of world data consumption but only 3% of data is stored in India. Why so, why can't we save our own data in our own country? Is any one working on it.

2 Replies

Sanskar

Keen Learner and Exp... • 1m

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