How to upload your project on GitHub 👇👇
https://news.1rj.ru/str/github_coding/37
Step by step approach explained
https://news.1rj.ru/str/github_coding/37
Step by step approach explained
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Essential Tools, Libraries, and Frameworks to learn Artificial Intelligence
1. Programming Languages:
Python
R
Java
Julia
2. AI Frameworks:
TensorFlow
PyTorch
Keras
MXNet
Caffe
3. Machine Learning Libraries:
Scikit-learn: For classical machine learning models.
XGBoost: For boosting algorithms.
LightGBM: For gradient boosting models.
4. Deep Learning Tools:
TensorFlow
PyTorch
Keras
Theano
5. Natural Language Processing (NLP) Tools:
NLTK (Natural Language Toolkit)
SpaCy
Hugging Face Transformers
Gensim
6. Computer Vision Libraries:
OpenCV
DLIB
Detectron2
7. Reinforcement Learning Frameworks:
Stable-Baselines3
RLlib
OpenAI Gym
8. AI Development Platforms:
IBM Watson
Google AI Platform
Microsoft AI
9. Data Visualization Tools:
Matplotlib
Seaborn
Plotly
Tableau
10. Robotics Frameworks:
ROS (Robot Operating System)
MoveIt!
11. Big Data Tools for AI:
Apache Spark
Hadoop
12. Cloud Platforms for AI Deployment:
Google Cloud AI
AWS SageMaker
Microsoft Azure AI
13. Popular AI APIs and Services:
Google Cloud Vision API
Microsoft Azure Cognitive Services
IBM Watson AI APIs
14. Learning Resources and Communities:
Kaggle
GitHub AI Projects
Papers with Code
Share with credits: https://news.1rj.ru/str/machinelearning_deeplearning
ENJOY LEARNING 👍👍
1. Programming Languages:
Python
R
Java
Julia
2. AI Frameworks:
TensorFlow
PyTorch
Keras
MXNet
Caffe
3. Machine Learning Libraries:
Scikit-learn: For classical machine learning models.
XGBoost: For boosting algorithms.
LightGBM: For gradient boosting models.
4. Deep Learning Tools:
TensorFlow
PyTorch
Keras
Theano
5. Natural Language Processing (NLP) Tools:
NLTK (Natural Language Toolkit)
SpaCy
Hugging Face Transformers
Gensim
6. Computer Vision Libraries:
OpenCV
DLIB
Detectron2
7. Reinforcement Learning Frameworks:
Stable-Baselines3
RLlib
OpenAI Gym
8. AI Development Platforms:
IBM Watson
Google AI Platform
Microsoft AI
9. Data Visualization Tools:
Matplotlib
Seaborn
Plotly
Tableau
10. Robotics Frameworks:
ROS (Robot Operating System)
MoveIt!
11. Big Data Tools for AI:
Apache Spark
Hadoop
12. Cloud Platforms for AI Deployment:
Google Cloud AI
AWS SageMaker
Microsoft Azure AI
13. Popular AI APIs and Services:
Google Cloud Vision API
Microsoft Azure Cognitive Services
IBM Watson AI APIs
14. Learning Resources and Communities:
Kaggle
GitHub AI Projects
Papers with Code
Share with credits: https://news.1rj.ru/str/machinelearning_deeplearning
ENJOY LEARNING 👍👍
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NumPy_SciPy_Pandas_Quandl_Cheat_Sheet.pdf
134.6 KB
Cheatsheet on Numpy and pandas for easy viewing 👀
ibm_machine_learning_for_dummies.pdf
1.8 MB
Short Machine Learning guide on industry applications and how it’s used to resolve problems 💡
1663243982009.pdf
349.9 KB
All SQL solutions for leetcode, good luck grinding 🫣
git-cheat-sheet-education.pdf
97.8 KB
Git commands cheatsheets for anyone working on personal projects on GitHub! 👾
1655183344172.pdf
333.8 KB
Algorithmic concepts for anyone who is taking Data Structure and Algorithms, or interested in algorithmic trading 😉
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Coding Projects
Print 'Y' Pattern in Python 👆
Pattern problems in Python are all about understanding loops and practicing different variations.
The key points to remember:
Outer Loop → Controls the number of rows.
Inner Loop → Controls the number of columns (or the number of elements in each row).
Logic Variation → Changing conditions in loops alters the pattern (e.g., printing stars, numbers, or alphabets).
Use of end=" " → Helps in formatting output on the same line instead of new lines.
Reverse Patterns → Requires manipulating loop ranges or decrementing values.
Using Conditional Statements (if-else) → Helps in complex patterns like hollow shapes.
Once you grasp these basics, it’s just about practice and creativity!
Hope it helps :)
The key points to remember:
Outer Loop → Controls the number of rows.
Inner Loop → Controls the number of columns (or the number of elements in each row).
Logic Variation → Changing conditions in loops alters the pattern (e.g., printing stars, numbers, or alphabets).
Use of end=" " → Helps in formatting output on the same line instead of new lines.
Reverse Patterns → Requires manipulating loop ranges or decrementing values.
Using Conditional Statements (if-else) → Helps in complex patterns like hollow shapes.
Once you grasp these basics, it’s just about practice and creativity!
Hope it helps :)
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Let's explore some of the best open source projects by language.
1⃣ Best Python Open Source Projects
🚣♂ TensorFlow
🚣♂ Matplotlib
🚣♂ Flask
🚣♂ Django
🚣♂ PyTorch
2⃣ Best JavaScript Open Source Projects
🚣♂ React
🚣♂ Node.JS
🚣♂ jQuery
3⃣ Best C++ Open Source Projects
🚣♂ Serenity
🚣♂ MongoDB
🚣♂ SonarSource
🚣♂ OBS Studio
🚣♂ Electron
4⃣ Best Java Open Source Projects
🚣♂ Mockito
🚣♂ Realm
🚣♂ Jenkins
🚣♂ Guava
🚣♂ Moshi
It's time to start developing your own open source projects. Explore the projects
1⃣ Best Python Open Source Projects
🚣♂ TensorFlow
🚣♂ Matplotlib
🚣♂ Flask
🚣♂ Django
🚣♂ PyTorch
2⃣ Best JavaScript Open Source Projects
🚣♂ React
🚣♂ Node.JS
🚣♂ jQuery
3⃣ Best C++ Open Source Projects
🚣♂ Serenity
🚣♂ MongoDB
🚣♂ SonarSource
🚣♂ OBS Studio
🚣♂ Electron
4⃣ Best Java Open Source Projects
🚣♂ Mockito
🚣♂ Realm
🚣♂ Jenkins
🚣♂ Guava
🚣♂ Moshi
It's time to start developing your own open source projects. Explore the projects
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