conda environments for Data Science and AI |A-Z in #urduhinditutorial

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Video Description:
Is video mein maine aapko step-by-step explain kiya hai conda environments kaise banaye jaate hai. Data science aur AI projects ke liye alag python environments maintain karna bohot zaruri hai. #conda #environments #datascience #aitools
Conda environments kaise banaye? Is video mein maine aapko conda environments banane ke liye puri detail mein process samjhaya hai. Maine pehle conda environments ki importance explain ki hai data science aur AI projects ke context mein. Maine bataya hai ki different projects ke liye alag dependencies aur versions ki requirement hoti hai, isliye har project ke liye alag python environment banana bohot beneficial hota hai.

Phir maine step-by-step conda env banane ka tutorial diya hai - conda create environment ka use, yml file banake environment define karna, and activate and deactivate karne ke commands. Maine envy bhi set karne ke steps bataye hai taki har baar activate karna na pade. Virtual environments ke benefits aur conda envs banane ke best practices pe bhi maine video mein detail mein guidance di hai.

Agar aap data science ya AI mein interested hai, toh yeh video aapke liye bohot useful hai. Video ko dekh ke aap conda env banane mein expert ban jaoge! #conda #environments #datascience #ai
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Very very good lecture, apk prhany k triqa bhutt Acha ha hum enjoy kr k prhty han😊 thanks a lot

Datascientist
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35:44 Libraries are collection of python codes (classes, functions) written by different developers around the globe that can be used to make our lifes easier ... (apna dimag thora kam istemal krna parta hai)...
Important Python Libraries: Pandas, Numpy, Matplotlib, Seaborn, Plotly, Streamlit, TensorFlow, Scikit Learn, Scipy, Math etc. etc.

fitfaizan
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Assignment no 5.
Important libraries in vs code for python

Pandas (With pandas, you can quickly read in data from a variety of sources, including CSV, Excel, and SQL databases. You can then use pandas to manipulate and transform your data, as well as to create useful visualizations, such as bar and line charts)

Numpy (Numpy is a Python library that allows you to do mathematical calculations very easily. It has many functions that allow you to perform these calculations.)

Seaborn (Seaborn is a library for making statistical graphics in Python. It builds on top of matplotlib and integrates closely with pandas data structures. Seaborn helps you explore and understand your data)

Matplot(One way to use plots in Visual Studio Code is with Juypiter notebooks, it’s useful to grasp the core concepts of matplotlib’s design)

Scikit-Learn (SKLEARN)(regression, clustering, and dimensionality reduction)

scipy ( It can operate an array of NumPy libraries and has also optimized the functions used in NumPy)

sanashah
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Python Libraries:
Pandas, Numpy, Scipy, Matplotlib, Seaborn, tensorflow, keras, schedule, plotly, pytorch

baigshahbaz
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I try my best but mara tensor flow env delete ni hoea

maryamarshad
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important libraries in python
numpy
matplotlib
scipy
tensorflow
pytorch
seaborn
statsmodel
plotly
scikit learn

sadiaali
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Python Important Libraries :
Numpy
Pandas
Matplotlib
Seaborn
Scipy
Statsmodel
Plotly
Scikit learn
Tensor flow
Pytorch

hassanqureshi