A collection of basic techniques for working with tensors in PyTorch — for those who are starting to get acquainted with the framework and want to quickly master its fundamentals.
What's inside:
A good starting material to understand the mechanics of tensors before moving on to models and training.▶️ What tensors are and why they are needed▶️ Tensor initialization: zeros, ones, random, similar size▶️ Type conversion and switching between NumPy and PyTorch▶️ Arithmetic, logical operations, tensor comparison▶️ Matrix multiplication and batch computations▶️ Broadcasting, view(), reshape(), changing dimensions▶️ Indexing and slicing: how to access parts of a tensor▶️ Notebook with code examples
tags: #useful
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1. Makes the first letter capitalized
.capitalize()
2. Lowers or raises the case of a string
.lower()
.upper()3. Centers the string with symbols around it: 'Python' → 'Python'
.center(10, '*')
4. Counts the occurrences of a specific character
.count('0')5. Finds the positions of specified characters
.find()
.index()
6. Searches for a desired object and replaces it
.replace()
7. Splits the string, removing the split point from it
.split()8. Checks what the string consists of
.isalnum()
.isnumeric()
.islower()
.isupper()tags: #useful
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📱 TorchCode — a PyTorch training tool for preparing for ML interviews
40 tasks for implementing operators and architectures that are actually asked in interviews. Automatic checking, hints, and reference solutions — all in the browser without installation.
If you're preparing for an ML interview, it's useful to go through at least half of them.
Link: https://github.com/duoan/TorchCode
tags: #useful #pytorch
https://t.me/CodeProgrammer✅
40 tasks for implementing operators and architectures that are actually asked in interviews. Automatic checking, hints, and reference solutions — all in the browser without installation.
If you're preparing for an ML interview, it's useful to go through at least half of them.
Link: https://github.com/duoan/TorchCode
tags: #useful #pytorch
https://t.me/CodeProgrammer
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🐼 Cheat Sheet on Data Wrangling — for everyone who works with Pandas
Everything you need is collected in one file: creating and merging DataFrames, filtering, grouping, handling missing values, and visualization.
It's convenient when you need to quickly refresh your syntax and don't want to dig into the documentation.
The cheat sheet in good quality
https://pandas.pydata.org/Pandas_Cheat_Sheet.pdf
tags: #useful
For more please ❤️
➡ https://t.me/CodeProgrammer
Everything you need is collected in one file: creating and merging DataFrames, filtering, grouping, handling missing values, and visualization.
It's convenient when you need to quickly refresh your syntax and don't want to dig into the documentation.
The cheat sheet in good quality
https://pandas.pydata.org/Pandas_Cheat_Sheet.pdf
tags: #useful
For more please ❤️
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Forwarded from Data Analytics
SQL Basics.pdf
102.8 KB
💻 Collection of cheat sheets on SQL
I've gathered for you short and understandable cheat sheets on the main topics:
▶️ Basics of the SQL language;
▶️ JOINs with clear examples;
▶️ Window functions;
▶️ SQL for data analysis.
An excellent set to refresh your knowledge before a job interview or quickly recall the syntax.
tags: #sql #useful
https://t.me/DataAnalyticsX
I've gathered for you short and understandable cheat sheets on the main topics:
▶️ Basics of the SQL language;
▶️ JOINs with clear examples;
▶️ Window functions;
▶️ SQL for data analysis.
An excellent set to refresh your knowledge before a job interview or quickly recall the syntax.
tags: #sql #useful
https://t.me/DataAnalyticsX
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📰 Awesome Open Source AI 2026 — A comprehensive collection of current open-source AI projects 🤖
This repository consolidates significant resources in a single location, including frameworks, training tools, inference utilities, RAG solutions, agents, and more. The content is organized into distinct categories to facilitate efficient navigation and resource identification for specific tasks. 📂
Repo: https://github.com/alvinreal/awesome-opensource-ai
Tags: #github #useful✔️
This repository consolidates significant resources in a single location, including frameworks, training tools, inference utilities, RAG solutions, agents, and more. The content is organized into distinct categories to facilitate efficient navigation and resource identification for specific tasks. 📂
Repo: https://github.com/alvinreal/awesome-opensource-ai
Tags: #github #useful
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