Essential Math for AI.pdf
18.1 MB
Essential Math for AI
Hala Nelson, 2022
Hala Nelson, 2022
Natural Language Processing with Transformers.pdf
6.4 MB
Natural Language Processing with Transformers
Lewis Tunstall, 2022
Lewis Tunstall, 2022
Cracking Codes with Python.pdf
7.6 MB
Cracking Codes with Python
Al Sweigart, 2018
Al Sweigart, 2018
hands-on-data-science.pdf
15.3 MB
Hands-On Data Science and Python Machine Learning
Frank Kane, 2017
Frank Kane, 2017
Synthetic Data for Machine Learning.pdf
7.7 MB
Synthetic Data for Machine Learning
Abdulrahman Kerim, 2023
Abdulrahman Kerim, 2023
sql.pdf_20231108_011916_0000.pdf
3.9 MB
SQL Practice Questions with Answers
Those who are at beginner and intermediate level in sql should try to solve all these question
Those who are at beginner and intermediate level in sql should try to solve all these question
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5⃣ Free DSA resources to crack coding interview
👉 GeekforGeeks
https://www.geeksforgeeks.org/the-ultimate-beginners-guide-for-dsa/amp/
👉 Leetcode
https://leetcode.com/study-plan/data-structure/
👉 Hackerrank
https://www.hackerrank.com/domains/data-structures
👉 Coding Interview Preparations
https://t.iss.one/crackingthecodinginterview/112
👉 FreeCodeCamp
https://www.freecodecamp.org/learn/javascript-algorithms-and-data-structures/
Join @free4unow_backup for more free courses
ENJOY LEARNING 👍👍
👉 GeekforGeeks
https://www.geeksforgeeks.org/the-ultimate-beginners-guide-for-dsa/amp/
👉 Leetcode
https://leetcode.com/study-plan/data-structure/
👉 Hackerrank
https://www.hackerrank.com/domains/data-structures
👉 Coding Interview Preparations
https://t.iss.one/crackingthecodinginterview/112
👉 FreeCodeCamp
https://www.freecodecamp.org/learn/javascript-algorithms-and-data-structures/
Join @free4unow_backup for more free courses
ENJOY LEARNING 👍👍
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Coding Projects in Python (DK).pdf
21.9 MB
Coding projects in Python
DK, 2017
DK, 2017
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15 Best Project Ideas for Backend Development : 🛠️🌐
🚀 Beginner Level :
1. 📦 RESTful API for a To-Do App
2. 📝 Contact Form Backend
3. 🗂️ File Upload Service
4. 📬 Email Subscription Service
5. 🧾 Notes App Backend
🌟 Intermediate Level :
6. 🛒 E-commerce Backend with Cart & Orders
7. 🔐 Authentication System (JWT/OAuth)
8. 🧑🤝🧑 User Management API
9. 🧾 Invoice Generator API
10. 🧠 Blog CMS Backend
🌌 Advanced Level :
11. 🧠 AI Chatbot Backend Integration
12. 📈 Real-Time Stock Tracker using WebSockets
13. 🎧 Music Streaming Server
14. 💬 Real-Time Chat Server
15. ⚙️ Microservices Architecture for Large Apps
Here you can find more Coding Project Ideas: https://whatsapp.com/channel/0029VazkxJ62UPB7OQhBE502
Web Development Jobs: https://whatsapp.com/channel/0029Vb1raTiDjiOias5ARu2p
JavaScript Resources: https://whatsapp.com/channel/0029VavR9OxLtOjJTXrZNi32
ENJOY LEARNING 👍👍
🚀 Beginner Level :
1. 📦 RESTful API for a To-Do App
2. 📝 Contact Form Backend
3. 🗂️ File Upload Service
4. 📬 Email Subscription Service
5. 🧾 Notes App Backend
🌟 Intermediate Level :
6. 🛒 E-commerce Backend with Cart & Orders
7. 🔐 Authentication System (JWT/OAuth)
8. 🧑🤝🧑 User Management API
9. 🧾 Invoice Generator API
10. 🧠 Blog CMS Backend
🌌 Advanced Level :
11. 🧠 AI Chatbot Backend Integration
12. 📈 Real-Time Stock Tracker using WebSockets
13. 🎧 Music Streaming Server
14. 💬 Real-Time Chat Server
15. ⚙️ Microservices Architecture for Large Apps
Here you can find more Coding Project Ideas: https://whatsapp.com/channel/0029VazkxJ62UPB7OQhBE502
Web Development Jobs: https://whatsapp.com/channel/0029Vb1raTiDjiOias5ARu2p
JavaScript Resources: https://whatsapp.com/channel/0029VavR9OxLtOjJTXrZNi32
ENJOY LEARNING 👍👍
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📈 Predictive Modeling for Future Stock Prices in Python: A Step-by-Step Guide
The process of building a stock price prediction model using Python.
1. Import required modules
2. Obtaining historical data on stock prices
3. Selection of features.
4. Definition of features and target variable
5. Preparing data for training
6. Separation of data into training and test sets
7. Building and training the model
8. Making forecasts
9. Trading Strategy Testing
The process of building a stock price prediction model using Python.
1. Import required modules
2. Obtaining historical data on stock prices
3. Selection of features.
4. Definition of features and target variable
5. Preparing data for training
6. Separation of data into training and test sets
7. Building and training the model
8. Making forecasts
9. Trading Strategy Testing
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