Epython Lab @epythonlab Channel on Telegram

Epython Lab

@epythonlab

Welcome to Epython Lab, where you can get resources to learn, one-on-one trainings on machine learning, business analytics, and Python, and solutions for business problems.

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Epython Lab (English)

Welcome to Epython Lab, a Telegram channel dedicated to providing resources for learning, one-on-one trainings on machine learning, business analytics, and Python, as well as solutions for business problems. Whether you are a beginner looking to learn the basics of Python or an experienced professional seeking to enhance your skills in machine learning, Epython Lab has something to offer for everyone.

The channel offers a variety of resources such as tutorials, guides, and tips to help you improve your knowledge and understanding of Python programming language. In addition, you can sign up for personalized one-on-one trainings with experts in the field to get the guidance and support you need to excel in your learning journey.

Epython Lab also provides practical solutions for real-world business problems, helping companies optimize their processes and make data-driven decisions. By leveraging the power of machine learning and business analytics, the channel aims to empower businesses with the tools they need to succeed in today's competitive market.

If you are looking to promote your products or services, Epython Lab offers advertising opportunities to reach a targeted audience interested in Python programming, machine learning, and business analytics. You can buy ads on the channel to showcase your offerings and connect with potential customers.

Join Epython Lab today to access valuable resources, training sessions, and solutions for your business needs. Start your journey towards mastering Python programming and leveraging the power of data to drive business success.

Epython Lab

12 Feb, 14:03

📌 Time Vs. Space Complexity | What's the difference? https://youtu.be/msVKyUnOjOU

Learn More About Algorithmic Thinking:

If you're interested in diving deeper into algorithmic problem-solving, check out these additional tutorials:

📌 Bubble Sort Algorithm Explained! Python Implementation & Step-by-Step Guide
https://www.youtube.com/watch?v=x6WGF8zDWZA

📌 Linear Search Algorithm: https://www.youtube.com/watch?v=f0KsENxdTGI

📌 Binary Search Algorithm: https://www.youtube.com/watch?v=_MjGCuwFDuw

🙏 Support My Work:
🎁 Send a thanks gift or become a member: https://www.youtube.com/channel/UCsFz0IGS9qFcwrh7a91juPg/join

💬 Join Our Telegram Discussion Group: https://t.me/epythonlab
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Epython Lab

11 Feb, 15:25

Learn more about Functions in Python 🐢 for beginners with examples
https://www.youtube.com/watch?v=DlTJbaVHM3c
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Epython Lab

10 Feb, 16:43

Introduction to dictionaries for beginners https://www.youtube.com/watch?v=C3QVeLXMiRI
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Epython Lab

09 Feb, 05:21

Enhancing Malaria Detection with Tiny Object Detection in Deep Learning

I’ve implemented a CNN-based malaria detection model, but detecting tiny infected red blood cells (RBCs) remains a challenge due to low contrast and scale variations in blood smear images.
To further improve accuracy, I plan to integrate Tiny Object Detection techniques, such as:
🔹 Feature Pyramid Networks (FPN) for better multi-scale feature extraction
🔹 Attention mechanisms to enhance focus on infected RBCs
🔹 Super-resolution methods for improved image clarity

Check out my current implementation on GitHub: https://github.com/epythonlab2/malaria_detection

Looking forward to exploring more advanced techniques in AI-powered healthcare! Let’s discuss—what are your thoughts? 👇
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Epython Lab

08 Feb, 17:00

Learn More About Algorithmic Thinking:

If you're interested in diving deeper into algorithmic problem-solving, check out these additional tutorials:

📌 Bubble Sort Algorithm Explained! Python Implementation & Step-by-Step Guide
https://www.youtube.com/watch?v=x6WGF8zDWZA

📌 Linear Search Algorithm: https://www.youtube.com/watch?v=f0KsENxdTGI

📌 Binary Search Algorithm: https://www.youtube.com/watch?v=_MjGCuwFDuw

🙏 Support My Work:
🎁 Send a thanks gift or become a member: https://www.youtube.com/channel/UCsFz0IGS9qFcwrh7a91juPg/join

💬 Join Our Telegram Discussion Group: https://t.me/epythonlab
549
Epython Lab

05 Feb, 14:55

Bubble Sort Algorithm Explained! Python Implementation & Step-by-Step Guide
https://www.youtube.com/watch?v=x6WGF8zDWZA
738
Epython Lab

03 Feb, 04:59

Learn More about Data Structures and Conditional Statements in Python:
📌 If statements, for loops, while loops: https://youtu.be/9k2rmxLtbNk
📌 Lists, Dictionaries, Tuples, File Handling: https://www.youtube.com/watch?v=lbdKQI8Jsok


🙏 Support My Work:
🎁 Send a thanks gift or become a member: https://www.youtube.com/channel/UCsFz0IGS9qFcwrh7a91juPg/join

💬 Join Our Telegram Discussion Group: https://t.me/epythonlab
816
Epython Lab

31 Jan, 04:43

Learn More About Algorithmic Thinking:
📌 Linear Search Algorithm: https://www.youtube.com/watch?v=f0KsENxdTGI
📌 Binary Search Algorithm: https://www.youtube.com/watch?v=_MjGCuwFDuw

🙏 Support My Work:
🎁 Send a thanks gift or become a member: https://www.youtube.com/channel/UCsFz0IGS9qFcwrh7a91juPg/join

💬 Join Our Telegram Discussion Group: https://t.me/epythonlab
964
Epython Lab

29 Jan, 15:33

Binary Search in simple way https://www.youtube.com/watch?v=_MjGCuwFDuw
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Epython Lab

27 Jan, 04:53

Data Structures full tutorial for beginners
https://www.youtube.com/watch?v=lbdKQI8Jsok

To create high-quality videos, I need support from 100 members. Please consider joining my membership tier for at least $1 per month. Your contributions will directly help me purchase essential equipment like a microphone. https://www.youtube.com/channel/UCsFz0IGS9qFcwrh7a91juPg/join



Join https://t.me/epythonlab for more learning resources
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Epython Lab

25 Jan, 10:47

To create high-quality videos, I need support from 100 members. Please consider joining my membership tier for at least $1 per month. Your contributions will directly help me purchase essential equipment like a microphone. https://www.youtube.com/channel/UCsFz0IGS9qFcwrh7a91juPg/join
891
Epython Lab

24 Jan, 09:05

Learn about Dictionary in Python 🐍 with examples

https://youtu.be/7N62qR2jLlA


#python #machinelearning #share
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Epython Lab

20 Jan, 14:11

Algorithmic thinking with linear search example https://www.youtube.com/watch?v=f0KsENxdTGI
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Epython Lab

17 Jan, 09:03

🐍 As we know Python is dynamically typed programming language. We do not need to statically define the type of data before we use it like other programming language such as c++ and java.

However, we could also statically indicate type hint for variables. You can learn here 👉👉https://youtu.be/x5wM5M6MJbU
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Epython Lab

14 Jan, 03:40

🐍 The most essential skill you must have as a Python Developer/Data Analyst/Data Scientist is membership operators.

In this short tutorial, you will learn about how to use membership operators in real world application.

👉👉https://youtu.be/Us-iQ_HbIrk

Subscribe, like, share 🙏
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Epython Lab

12 Jan, 07:43

As a Developer, the best practice is writing clean, simple, concise, and readable code.

Learn about how to write clean code  https://youtu.be/upe7v7dhv0Y

Sharing is caring 🙏
1,036
Epython Lab

09 Jan, 07:15

Functions in Python 🐢 for beginners with examples
https://www.youtube.com/watch?v=DlTJbaVHM3c

Local and global scope of functions https://www.youtube.com/watch?v=jJv-aFaddNw

Parameters vs positional arguments? https://www.youtube.com/watch?v=K-u3vndXulg
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Epython Lab

09 Jan, 03:24

A technique used to extract features from the text. It counts how many times a word appears in a document (corpus), and then transforms that information into a dataset.
https://youtu.be/tn-Tvi8CHmg
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Epython Lab

08 Jan, 16:43

Creating and parsing XML documents in Python is valuable for managing and exchanging structured data. In this tutorial, you'll cover the basics of creating and parsing XML documents using Python's built-in XML module.

https://www.youtube.com/watch?v=WnbS90EzU0Y
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Epython Lab

04 Jan, 12:09

🐍 POP QUIZ | Day 5: What type of module is the OS in Python?

Learn about handling files using the OS module in Python https://youtu.be/aWB3Ubb1UV0

@epythonlab #popquiz
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Epython Lab

01 Jan, 16:53

Happy print(sum(i**3 for i in range(10)))

Source: Andrew NG(The god father of AI)

Learn Python from scratch https://youtu.be/ISv6XIl1hn0
Join our telegram to get resources https://t.me/epythonlab
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Epython Lab

31 Dec, 06:27

HAPPY NEW YEARS! MAY ALL YOUR DREAMS COME TRUE FOR 2025!
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Epython Lab

30 Dec, 16:04

A step-by-step tutorial on how to build and publish your Python library https://youtu.be/ZQlDrNvQn6Y



Join our telegram https://t.me/epythonlab



Subscribe to our YouTube https://youtube.com/epythonlab
885
Epython Lab

28 Dec, 15:56

Learn genetic algorithms by solving Fibonacci sequences

https://www.youtube.com/watch?v=9M4ETVngWy4&list=PL0nX4ZoMtjYHV6n2-0taITMZlrd23hKL1&index=2
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Epython Lab

28 Dec, 08:25

🌟𝘿𝙖𝙮 25/100: 𝙐𝙣𝙙𝙚𝙧𝙨𝙩𝙖𝙣𝙙𝙞𝙣𝙜 𝙀𝙩𝙝𝙞𝙤𝙥𝙞𝙖𝙣 𝙁𝙞𝙣𝙩𝙚𝙘𝙝 🌟



Ethiopia's fintech ecosystem is a mix of challenges and opportunities. 📈🌍

From low formal banking penetration to an increasingly digital population, it’s clear that innovation in financial services is critical.



Key insights from my research today:

- Low banking penetration but high mobile adoption: Over 75% of transactions are cash-based, yet mobile payment systems like Telebirr are gaining traction.

- Regulatory frameworks: Ethiopia’s regulatory approach emphasizes financial inclusion but poses innovation challenges, especially for Buy-Now-Pay-Later services.

- Unique consumer behaviors: The dominance of informal financial systems and cash reliance shapes how Ethiopians engage with digital financial services.



💡 Question of the day: How can fintech drive financial literacy in Ethiopia to accelerate digital adoption?



#FintechAfrica #Ethiopia #Buy-Now-Pay-Later #FinancialLiteracy #DigitalTransformation
646
Epython Lab

27 Dec, 07:25

🌟𝘿𝙖𝙮 24/100: 𝙉𝙚𝙭𝙩 𝙎𝙩𝙚𝙥𝙨 𝙛𝙤𝙧 𝘾𝙚𝙣𝙩𝙧𝙖𝙡𝙞𝙯𝙚𝙙 𝙀-𝙘𝙤𝙢𝙢𝙚𝙧𝙘𝙚🌟



I'm moving closer to deploying a centralized e-commerce platform for Ethiopia.



Next steps:

1️⃣ Integrating XLM-Roberta for real-time entity extraction.

2️⃣ Expanding the dataset for even better performance.

3️⃣ Collaborating with vendors to enrich product listings.



💡 Takeaway: NLP-driven platforms like central e-commerce can redefine how e-commerce works in Ethiopia.



💡 Discussion: How can we scale similar platforms for other underrepresented markets?

#AI #ECommerce #FintechAfrica #Amharic
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Epython Lab

26 Dec, 06:55

I am excited to share with you the Python Programming for Beginners roadmap

Basic Python Programming: https://youtu.be/ISv6XIl1hn0

Data Structures with Projects full tutorial for beginners
https://www.youtube.com/watch?v=lbdKQI8Jsok

OOP in Python - beginners Crash Course https://www.youtube.com/watch?v=I7z6i1QTdsw

Join #epythonlab https://t.me/epythonlab

Join https://t.me/epythonlab for more learning resources
635
Epython Lab

26 Dec, 05:13

🌟 𝘿𝙖𝙮 23/100: 𝙏𝙧𝙪𝙩𝙝 𝙤𝙧 𝙇𝙞𝙚: 𝙉𝙖𝙫𝙞𝙜𝙖𝙩𝙞𝙣𝙜 𝙅𝙤𝙗 𝙄𝙣𝙩𝙚𝙧𝙫𝙞𝙚𝙬𝙨 🌟

This morning, I received an exciting email: "Interview Invitation: AI Python and .NET Developer."

While I’m proficient in AI Python and have tackled many projects, .NET isn’t in my skill set. I faced a dilemma:

Exaggerate my expertise?
Or be honest about my strengths and gaps?
I chose truth. I emphasized my Python expertise and willingness to learn .NET.

💡 Lesson: Honesty builds trust and keeps doors open for the right opportunities.

Have you faced a similar situation? Let’s discuss in the comments! 🙌
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Epython Lab

25 Dec, 15:01

Build Secure Password Generator: Tkinter Project https://www.youtube.com/watch?v=5XpcnqhgikM
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Epython Lab

25 Dec, 05:49

📢𝘿𝙖𝙮 22/100: 𝙏𝙝𝙚 𝙑𝙖𝙡𝙪𝙚 𝙤𝙛 𝘾𝙚𝙣𝙩𝙧𝙖𝙡𝙞𝙯𝙚𝙙 𝘿𝙖𝙩𝙖

Why is centralizing e-commerce data critical for Ethiopia?



- For vendors: Better visibility and reach.

- For customers: Streamlined product discovery.

- For analytics: Real-time insights into market trends.



💡 Question: What are the key challenges to centralizing data in emerging markets?

#ECommerce #DigitalTransformation #Ethiopia
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Epython Lab

24 Dec, 07:57

Learn Object Oriented in Python - beginners Crash Course https://www.youtube.com/watch?v=I7z6i1QTdsw

Help us fill out this survey https://forms.gle/vEppeY3yy3WQeUx86

Join https://t.me/epythonlab
664
Epython Lab

24 Dec, 06:26

📢𝗗𝗮𝘆 𝟮𝟭/𝟭𝟬𝟬: 𝗧𝗿𝗮𝗶𝗻𝗶𝗻𝗴 𝗔𝗺𝗵𝗮𝗿𝗶𝗰 𝗡𝗘𝗥 𝗠𝗼𝗱𝗲𝗹𝘀

I fine-tuned models on 27,989 labeled examples, optimizing key parameters:

- Learning rate: Experimented to find the sweet spot.

- Batch size: Limited to 16 to manage memory constraints.

- Metrics: Focused on precision, recall, and F1-score.



💡 Finding: Smaller batches helped balance performance and computational efficiency.

💡 Question: How do you optimize parameters for low-resource NLP tasks?

#AI #ModelTraining #Ethiopia #NLP
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Epython Lab

23 Dec, 17:40

15 𝘽𝙚𝙨𝙩 𝙋𝙮𝙩𝙝𝙤𝙣 𝘼𝙄/ 𝙈𝙖𝙘𝙝𝙞𝙣𝙚 𝙇𝙚𝙖𝙧𝙣𝙞𝙣𝙜 𝙋𝙧𝙤𝙟𝙚𝙘𝙩𝙨 𝙩𝙤 𝘽𝙤𝙤𝙨𝙩 𝙔𝙤𝙪𝙧 𝙎𝙠𝙞𝙡𝙡𝙨 https://medium.com/p/96677345b57d
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Epython Lab

23 Dec, 16:03

𝘼𝙄 𝙄𝙨 𝙍𝙚𝙫𝙤𝙡𝙪𝙩𝙞𝙤𝙣𝙖𝙧𝙮, 𝘽𝙪𝙩 𝘼𝙧𝙚 𝙒𝙚 𝙊𝙫𝙚𝙧𝙡𝙤𝙤𝙠𝙞𝙣𝙜 𝙌𝙪𝙖𝙣𝙩𝙪𝙢 𝘾𝙤𝙢𝙥𝙪𝙩𝙞𝙣𝙜?
In the tech world, discussions of Artificial Intelligence dominate the stage—and rightly so. AI has transformed industries, revolutionized how we work, and opened the door to possibilities once thought unattainable.
But here’s a question for the experts: Are we paying enough attention to quantum computing?
Quantum computing isn't just a buzzword; it has the potential to supercharge AI by solving problems that classical computers can’t handle in a practical timeframe. From optimizing complex systems to enabling breakthroughs in drug discovery and cryptography, the synergy between AI and quantum computing could redefine innovation.
Yet, in many discussions about AI, I rarely hear about how we’re preparing for this convergence.
How do we ensure our AI models are ready to harness quantum power?
What are the ethical considerations as we bridge these two transformative technologies?
To those immersed in AI, have you explored the potential of quantum computing in your field? If not, why? Let’s start a conversation about how these technologies can shape the future—together.

hashtag#AI hashtag#QuantumComputing hashtag#Innovation hashtag#FutureTech https://medium.com/@epythonlab/whats-next-after-ai-the-emerging-frontiers-of-technology-822c73b9c7c9
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Epython Lab

23 Dec, 06:07

📢Day 20/100: Overcoming Tokenization Challenges
Tokenization is critical for NLP tasks like Named Entity Recognition.

Key steps:
1️⃣ Aligning tokens with Amharic text.
2️⃣ Preserving the relationship between tokens and their labels.
3️⃣ Using model-specific tokenizers (XLM-Roberta, mBERT).

💡 Takeaway: Tokenization errors can significantly impact the accuracy of entity recognition models.

#AI #Tokenization #AmharicNLP #FintechInnovation
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Epython Lab

22 Dec, 10:06

📢Day 19/100: Choosing the Right Language Model

For Amharic Named Entity Recognition, we fine-tuned three models:

1️⃣ XLM-Roberta: Best for multilingual NLP.

2️⃣ mBERT: Balanced performance.

3️⃣ DistilBERT: Lightweight but slightly less accurate.

💡 Insight: XLM-Roberta outperformed others in accuracy and entity recognition for Amharic e-commerce data.

💡 Question: What’s your experience with fine-tuning NLP models for underrepresented languages?

#AI #NLP #ModelSelection #FintechAfrica
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Epython Lab

20 Dec, 17:02

Python Data Structures for absolute beginners with Project
https://www.youtube.com/watch?v=lbdKQI8Jsok
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Epython Lab

20 Dec, 04:37

📢Day 18/100: Labeling Amharic Text for NER

Labeling Amharic text for Named Entity Recognition is no small task.

Our algorithm identifies:

Prices using patterns like "ብር" (currency).

Locations from a predefined list.

Products through contextual analysis.

💡 Example: "ዋጋ 4800 ብር" -> "B-PRICE I-PRICE I-PRICE"

💡 Discussion: How can we simplify labeling entities in low-resource languages?

#NER #Amharic #DataLabeling #Ethiopia
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Epython Lab

19 Dec, 04:39

📢Day 17/100: From Data to Insights



My journey started with collecting and cleaning data from Telegram channels, a hub for Ethiopian e-commerce.



Key steps:

1️⃣ Scraping Telegram messages to capture product details.

2️⃣ Preprocessing Amharic text to handle non-text characters and normalize content.

3️⃣ Tokenizing text for labeling.



💡 Takeaway: High-quality data preparation is the backbone of effective machine learning models.


#DataScience #AmharicNLP #FintechEthiopia
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Epython Lab

18 Dec, 09:55

📢Day 16/100: Tackling Amharic NLP Challenges

Amharic presents unique challenges in natural language processing (NLP), from its complex script to a lack of annotated datasets.



My approach: Fine-tune Large Language Models (LLMs) for Amharic Named Entity Recognition (NER) to extract product names, prices, and locations from Telegram messages.



💡 Discussion: What strategies can we adopt to make NLP more accessible for low-resource languages like Amharic?

#NLP #AI #Amharic #FintechEthiopia
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Epython Lab

17 Dec, 11:24

📢Day 15/100: The Rise of Telegram E-Commerce in Ethiopia

Telegram is transforming e-commerce in Ethiopia, but its fragmented nature poses challenges. Vendors operate in silos, and customers struggle to navigate multiple channels.



EthioMart's Vision:



We aim to create a centralized platform aggregating data from Telegram channels, simplifying product discovery for customers and enhancing visibility for vendors.



💡 Question of the day: How can centralized platforms improve Ethiopia’s digital shopping experience?





#Ethiopia #ECommerce #DigitalTransformation #Telegram #FintechInnovation
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Epython Lab

16 Dec, 11:48

Please kindly request you to fill this survey. We will not take your personal information.
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Epython Lab

16 Dec, 05:31

📢Day 14/100: Next Steps for the Credit Scoring Model

With the prototype complete, here’s what’s next:

1️⃣ Testing with real-world data: Partnering with fintechs to validate the model.

2️⃣ Incorporating mobile money data: Adding another dimension to the scoring process.

3️⃣ Monitoring and retraining: Ensuring the model stays relevant as new data comes in.

💡 Takeaway: A successful model is never truly done—it evolves with the market.

💡 Question: What’s your approach to maintaining machine learning models in production?

#CreditScoring #MachineLearning #FintechEthiopia #AI
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Epython Lab

15 Dec, 05:38

📢Day 13/100: Real-World Prototype Deployment

The prototype for my credit scoring model is live! 🚀

Features:

1️⃣ Web dashboard: Enter customer details and get real-time risk classifications.

2️⃣ API integration: Seamless communication between the frontend and back end.

3️⃣ Explainable results: Each score is accompanied by a breakdown of contributing factors.

💡 Takeaway: Deploying a functional prototype provides valuable feedback for real-world usability.

💡 Question: How do you ensure user-friendly designs for fintech tools in emerging markets?

#Prototype #AI #FintechEthiopia #CreditScoring
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Epython Lab

14 Dec, 14:05

Build a self-evolving Genetic Algorithm
https://youtu.be/9M4ETVngWy4
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Epython Lab

14 Dec, 09:28

📢Day 12/100: Comparing Machine Learning Models

Today, I compared the performance of multiple machine learning models for credit scoring:

1️⃣ Logistic Regression: Simple and interpretable but less effective with complex data.

2️⃣ Random Forest: Excellent for feature importance but slower for large datasets.

3️⃣ Gradient Boosting: Best overall performance with high accuracy and recall.

💡 Finding: Gradient Boosting stood out with an ROC-AUC of 0.97.

💡 Question: Do you prioritize interpretability or accuracy when selecting a model for financial applications?

#MachineLearning #ModelSelection #CreditScoring #FintechEthiopia
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Epython Lab

13 Dec, 11:13

📢Day 11/100: Integrating AI and ML in Credit Scoring

AI and machine learning are at the heart of my credit scoring model, but they require careful application. 🤖

Today’s focus:

1️⃣ Modeling approaches: Exploring supervised learning techniques like Gradient Boosting for risk prediction.

2️⃣ Bias mitigation: Addressing imbalances in transactional data to ensure fair outcomes.

3️⃣ Explainability: Building a model that’s transparent and interpretable to meet regulatory standards.

💡 Coming soon: Detailed performance metrics and insights from my initial experiments with AI-powered credit scoring!

#AI #MachineLearning #CreditScoring #ExplainableAI #FintechEthiopia
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Epython Lab

12 Dec, 13:43

📢Day 10/100: Class Imbalance Challenges
Class imbalance is a persistent issue in fraud detection and credit scoring. 🚨

In my dataset:

Fraudulent transactions are rare (<5%), making prediction tricky.
Techniques like SMOTE (Synthetic Minority Oversampling Technique) helped balance the dataset.
💡 Key Insight: Balancing the data improved model precision for rare classes like fraud detection.

💡 Question: What other methods do you use to address class imbalance without oversampling?

#DataChallenges #FraudDetection #CreditScoring #FintechInnovation
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Epython Lab

07 Dec, 06:07

📢Day 5/100: Understanding Ethiopian Fintech

Ethiopia's fintech ecosystem is a mix of challenges and opportunities. 📈🌍

From low formal banking penetration to an increasingly digital population, it’s clear that innovation in financial services is critical.

Key insights from my research today:

1️⃣ Low banking penetration but high mobile adoption: Over 75% of transactions are cash-based, yet mobile payment systems like Telebirr are gaining traction.

2️⃣ Regulatory frameworks: Ethiopia’s regulatory approach emphasizes financial inclusion but poses innovation challenges, especially for BNPL services.

3️⃣ Unique consumer behaviors: Ethiopians' dominance of informal financial systems and cash reliance shape their engagement with digital financial services.

💡 Question of the day: How can fintech drive financial literacy in Ethiopia to accelerate digital adoption?

#FintechAfrica #Ethiopia #BNPL #FinancialLiteracy #DigitalTransformation
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Epython Lab

06 Dec, 04:17

📢 Day 4/100: The Role of Data in Credit Scoring

Data is the fuel for any credit scoring engine. 🔍

However, in Ethiopia, traditional credit data is scarce.

Today, I'll dive into:

Types of alternative data (e.g., mobile money, e-commerce behavior).

Ethical challenges in data collection.

I plan to build a framework that respects privacy while being effective.

#DataDriven #CreditScoring #AlternativeData #Fintech #EthicalAI #Ethiopia
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Epython Lab

05 Dec, 05:20

📢 Day 3: Using RFM Scoring to Classify Customer Risk
📊 Before diving into machine learning or deep learning models, I started with a simpler yet powerful approach: RFM (Recency, Frequency, Monetary) scoring to classify customers into high-risk or low-risk groups.
Why RFM? In the context of Ethiopian BNPL services, where traditional credit histories are scarce, RFM provides a practical starting point by analyzing customer behavior:
1️⃣ Recency: How recently did the customer make a purchase?
2️⃣ Frequency: How often do they shop?
3️⃣ Monetary: How much do they spend?
This method helped me:
✅ Identify behavioral patterns to differentiate reliable customers from risky ones.
✅ Create a foundation for more advanced models
✅ Address data scarcity by leveraging transactional and engagement data.
RFM scoring is simple and interpretable, making it easier to communicate results to stakeholders early on.Next, I’ll integrate these insights into machine learning models to refine predictions and enhance scalability. 🚀
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Epython Lab

04 Dec, 08:09

What’s Next After AI? The Emerging Frontiers of Technology https://medium.com/@epythonlab/whats-next-after-ai-the-emerging-frontiers-of-technology-822c73b9c7c9
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Epython Lab

04 Dec, 05:35

📢 Day 2/100: Why BNPL in Ethiopia?



BNPL services have huge potential in Ethiopia, a country with growing digital adoption but limited formal credit access. 🛒💳

Key points I'll focus on:

1️⃣ Addressing financial inclusion.

2️⃣ Navigating unique local challenges (e.g., data availability).

3️⃣ Leveraging tech for scalability.



What do you think are the biggest opportunities for BNPL in emerging markets?



#BNPL #EmergingMarkets #FintechInnovation #DigitalFinance #Ethiopia #FinancialInclusion
412
Epython Lab

03 Dec, 06:20

Day 1: Introduction to the Challenge
📢 Day 1/100: The Journey Begins!
I'm embarking on a 100-day challenge to share insights, progress, and lessons learned as I build a data-driven credit scoring model tailored for Buy-Now-Pay-Later (BNPL) services in Ethiopia's fintech space. 🚀

Why this topic? BNPL is reshaping financial inclusion, and robust credit scoring is the backbone of sustainable lending. Follow along as I explore data, algorithms, and strategies to make this happen!

hashtag#Fintech hashtag#DataScience hashtag#CreditScoring hashtag#BNPL hashtag#FinancialInclusion hashtag#Ethiopia hashtag#100DaysChallenge
469
Epython Lab

02 Dec, 17:37

Help us by filling this form https://forms.gle/vEppeY3yy3WQeUx86
482
Epython Lab

01 Dec, 13:41

Developer Skills, AI Impact, and the Future of Software Careers

This survey aims to assess developers' skill levels, usage of AI tools like ChatGPT, and perspectives on the future of AI in the software development field. We also want to understand your favorite programming languages and the reasons behind your preferences.

The collected data will be used exclusively for research and educational purposes to better understand developer challenges and career trends. Your participation is voluntary, and no information provided will be used for illegal activities. All responses will remain confidential.
https://forms.gle/vEppeY3yy3WQeUx86
634
Epython Lab

01 Dec, 08:30

Simplify Your Python Code with Dictionary Default Values! 🚀🐍

Did you know you can avoid repetitive conditional checks in Python when working with dictionaries?

Instead of manually handling missing keys, use the `defaultdict` from the collections module.

It’s a game-changer!

💡 Why use it?

- No need for if-else or get() checks to handle missing keys.

- Perfect for counting items, grouping data, or setting up default values.
541
Epython Lab

30 Nov, 13:41

Check out our AI Projects
https://github.com/epythonlab2
607
Epython Lab

29 Nov, 12:27

The hidden costs of data quality issues in Machine Learning
https://youtu.be/TdMu-0TEppM
678
Epython Lab

25 Nov, 09:45

What are the concepts behind list, tuple, and dictionary?

This tutorial will give you an insight about them
https://youtu.be/YYzOGQCBUjo
883
Epython Lab

25 Nov, 05:33

Top 10 Pandas Functions to Filter Data Like a Pro (Step-by-Step Guide)
https://medium.com/@epythonlab/top-10-pandas-functions-to-filter-data-like-a-pro-step-by-step-guide-536ac28cac7a
754
Epython Lab

22 Nov, 06:21

A New Mojo Programming Language for Machine Learning- Full Course for Beginners
https://youtu.be/pyfCTxKcDPY

Join #epythonlab https://t.me/epythonlab
906
Epython Lab

18 Nov, 15:51

Beginner's Guide to Python Programming. Getting started now: https://youtu.be/ISv6XIl1hn0

Data Structures with Projects full tutorial for beginners
https://www.youtube.com/watch?v=lbdKQI8Jsok

OOP in Python - beginners Crash Course https://www.youtube.com/watch?v=I7z6i1QTdsw

Join #epythonlab https://t.me/epythonlab

Join https://t.me/epythonlab for more learning resources
1,086
Epython Lab

16 Nov, 03:07

can I learn Python and get a job without degree certificate?

https://youtu.be/Ps9sqmgFhmU
956
Epython Lab

13 Nov, 04:30

How fast is built-in sorting function
@epythonlab #short_codes
943
Epython Lab

11 Nov, 11:26

3 most commonly used string formatting
https://youtu.be/d6K5u5S9wn4
924
Epython Lab

10 Nov, 09:10

This is a step by step web scrapping tutorials from scratch
👉Learn how to scrape data from any website for data analysis
https://www.youtube.com/playlist?list=PL0nX4ZoMtjYESrtqb0zrOoDkS5XskWB25

👉Join Telegram https://t.me/epythonlab/

#python #data #webscraping #epythonlab
931
Epython Lab

07 Nov, 15:12

Getting data from webpage and transform it to structure format for data analysis is one of the skills that you need to have 🐍🐍

This is a step by step tutorials of scraping and transforming table data from website https://lnkd.in/dJzB36HQ

Join Telegram https://t.me/epythonlab/

#epythonlab #python #webscraping
890
Epython Lab

06 Nov, 02:27

Harry up 😁 programmers is increasing linearly.



According to the #bardai search results, programmers are expected to be 30 million in 2024 in the world workforce.



This is amazing for newbies.



Data source: bardai

Visualization is done by @asibehtenager

#visualization #data

Join https://t.me/epythonlab/ for more resources
881
Epython Lab

04 Nov, 05:18

Unpacking variables is very efficient way yo write clean code in Python
Take a look at the below links to get understand about iterable unpacking

Extended Iterable Unpacking in Python

#python #Subscribe #youtubechannel

https://youtu.be/BluC5ByjiJI
871
Epython Lab

02 Nov, 08:11

I'm curious🤭 about statistics Vs Probability
Here, I have made some tutorials about probability distribution for Machine learning using Scipy Python library https://www.youtube.com/watch?v=TkFipAuH-rY&list=PL0nX4ZoMtjYEl_1ONxAZHu65DPCQcsHmI
946
Epython Lab

28 Oct, 12:12

Check the github repositories for other AI projects
https://github.com/epythonlab
1,147
Epython Lab

28 Oct, 11:57

Fraud Detection for E-commerce and Bank

Github

Report

This project leverages machine learning to detect fraudulent transactions in e-commerce and banking, aiding in proactive security and risk management. The goal is to provide a robust fraud detection pipeline with explainability, deployment, and dashboard visualization for actionable insights.
1,153
Epython Lab

26 Oct, 09:37

As a data scientist 70-80 percent of your time spending on data cleansing. If you have given data which contains special characters and you may need to avoid those special characters, what methods do you use to avoid it?
https://youtu.be/qL7lX5lCfgw
953
Epython Lab

25 Oct, 14:42

What are membership in Python?

https://youtu.be/Us-iQ_HbIrk

Buy me coffee(1$) https://www.youtube.com/channel/UCsFz0IGS9qFcwrh7a91juPg/join
971
Epython Lab

25 Oct, 08:19

Flask is my number 1 choice due to flexibility(API development)

Plotly + Dash is awesome(Front end)

I will share the full implementations with documentation by Next week

Stay Tuned
1,103
Epython Lab

23 Oct, 13:47

Join Our Telegram Group for Python Resources!
Find Python blogs, tutorials, challenges, and more.
https://t.me/epythonlab
945
Epython Lab

23 Oct, 07:07

Thank you for participating in buy me coffee(1$) YouTube Membership

https://www.youtube.com/channel/UCsFz0IGS9qFcwrh7a91juPg/join
891
Epython Lab

22 Oct, 10:30

Deep Learning Models Hagging my CPU 😁
913
Epython Lab

22 Oct, 05:32

Danger of Statistics

"I never believe in statistics
I didn't doctor myself" Winston Churchill Said

Statistics: is deep and manipulated
Understand how to turn RAW DATA ===> Decision/Conclusion
@epythonlab
612
Epython Lab

21 Oct, 05:22

Website Scraper App with Flask and Python
https://youtu.be/EM9upHH-dTU
Test it and give feedback
https://blddemo.herokuapp.com
651
Epython Lab

20 Oct, 10:24

Data structures for beginners - Lists and How to manipulate data in lists
https://www.youtube.com/watch?v=yciXebzkjpw
499
Epython Lab

19 Oct, 08:05

The highest fraud rate in the world

Report
694
Epython Lab

18 Oct, 09:22

🖥 What is the output of the following code?

➕solution here:https://www.youtube.com/watch?v=jJv-aFaddNw

👉Join Telegram https://t.me/epythonlab/

#python #shorts #pythontricks #epythonlab #projects
733
Epython Lab

17 Oct, 10:08

Mathematics for Machine Learning RoadMap

🔗 Link to Linear Regression https://bit.ly/46rqiBu
🔗 Link to Linear Algebra https://bit.ly/45EpfwB
🔗 Link to Probability Distribution https://bit.ly/495L8b5
🔗 Link to Telegram Group https://bit.ly/3IR1lnm
724
Epython Lab

17 Oct, 05:11

Data structures for beginners - Lists and How to manipulate data in lists
https://www.youtube.com/watch?v=yciXebzkjpw
534
Epython Lab

15 Oct, 14:46

Build Medical Data Warehouse using ETL/ELT and Computer Vision(YoLOVx)

Report

Github Link
780
Epython Lab

15 Oct, 13:12

This is how computer vision help to build data warehouse
775
Epython Lab

14 Oct, 13:27

Create Dictionary Easy Made

👉Learn More Python Tips and Tricks: https://bit.ly/Pythontoptips

👉Join Telegram https://t.me/epythonlab/

#python #shorts #pythontricks #epythonlab
824
Epython Lab

13 Oct, 11:40

Reading and Analyzing DNA Sequences with Python
https://www.youtube.com/watch?v=i7rXa2nHjUg
767
Epython Lab

13 Oct, 06:21

What does if 'name=='main': do?

Learn More Python Tricks: https://bit.ly/45QI3JX

👉Join Telegram https://t.me/epythonlab/

#python #shorts #pythontricks #epythonlab
704
Epython Lab

12 Oct, 20:10

🖥 Which are positional arguments?

➕Check out solution here:https://www.youtube.com/watch?v=K-u3vndXulg

👉Join Telegram https://t.me/epythonlab/

#python #shorts #pythontricks #epythonlab #projects
588
Epython Lab

12 Oct, 11:59

Day 8: Do you know the difference between parameters vs positional arguments?
Check out this tutorial https://www.youtube.com/watch?v=K-u3vndXulg
669
Epython Lab

12 Oct, 07:39

🚀 Transforming Ethiopian Telegram E-Commerce with LLMs 🌍
https://www.linkedin.com/feed/update/urn:li:activity:7250769167136481280/
504
Epython Lab

12 Oct, 07:37

Meet Asibeh Tenager on LinkedIn
https://www.linkedin.com/in/asibehtenager/
494
Epython Lab

11 Oct, 10:05

Artificial Intelligence in a modern approach
Download Ebook

@epythonlab
629
Epython Lab

11 Oct, 10:01

Numpy🥰 is the most popular library used to manipulate numerical data

Here is a tutorial, to perform statistical analysis of your data
👉 https://youtu.be/cb_-745LZpg
515
Epython Lab

11 Oct, 05:10

😘How do you reduce complexity of Dictionary data while searching in Python?
Fore more 👉https://youtu.be/tB6VDz4kwxY

🥰🥰 Follow Epython Lab for more contents 🥰
#complexity #data #python #machinelearning
535
Epython Lab

10 Oct, 20:02

Python as an ETL tool? ETL Process Pipeline with Python: https://youtu.be/3J1D33US7NM

Test ETL Pipeline: https://youtu.be/78x6V5q34qs
541
Epython Lab

10 Oct, 06:01

Free Python Tools #datascience #machinelearning #artificialintelligence
614
Epython Lab

09 Oct, 18:00

✅TIP

Indentation is important for python programming you never miss it.

Indentation refers to the spaces at the beginning of a code line.

Where in other programming languages the indentation in code is for readability only, the indentation in Python is very important.

Python uses indentation to indicate a block of code.
Example:
for x in range (2, 5):
print x

N.B: Python will give you an error if you skip the indentation:

EXAMPLE:
for x in 5:
print x
538
Epython Lab

08 Oct, 19:21

Streamline Real-time amharic messaging from ecommerence telegram channels (Large Language Model)

Report Github Link
654
Epython Lab

08 Oct, 19:10

Credit Scoring Model

Report Github Link
686
Epython Lab

08 Oct, 06:52

Python data structures, Excel/CSV files, and MySQL in terms of storage
and manipulation:
760

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