Master #DataAnalytics for real-world problems. I have curated a list of 40 Data Analytics Projects (solved & explained) that will help you build analytics skills using #Python.

Includes projects like:

1. Rainfall Trends in India Analysis
2. Netflix Content Strategy Analysis
3. Creating a Mutual Fund Plan
4. Stock Market Portfolio Optimization
5. Metro Operations Optimization
6. Analyzing the Impact of Carbon Emissions

Find this list of projects here:
https://thecleverprogrammer.com/2024/11/01/data-analytics-projects-with-python/

📂 Tags: #DataScience #Python #ML #AI #LLM #BIGDATA #Courses #Pandas #deeplearning #Projects

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Best LLMs Courses

Link: https://www.mltut.com/best-large-language-models-courses/

#MachineLearning #DeepLearning #BigData #Datascience #ML #HealthTech #DataVisualization #ArtificialInteligence #SoftwareEngineering #GenAI #deeplearning #ChatGPT #OpenAI #python #AI #keras #SQL #Statistics #LLMs #AIagents

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🐼 20 of the most used Pandas + PDF functions

👨🏻‍💻 The first time I used Pandas, I was supposed to quickly clean and organize a raw and complex dataset with the help of Pandas functions. Using the groupby function, I was able to categorize the data and get in-depth analysis of customer behavior. Best of all, it was when I used loc and iloc that I could easily filter the data.

✔️ Since then I decided to prepare a list of the most used Pandas functions that I use on a daily basis. Now this list is ready! In the following, I will introduce 20 of the best and most used Pandas functions:



🏳️‍🌈 read_csv(): Fast data upload from CSV files

🏳️‍🌈 head(): look at the first five rows of the database to start..

🏳️‍🌈 info(): Checking data structure such as data type and empty values.

🏳️‍🌈 describe(): Generate descriptive statistics for numeric columns.

🏳️‍🌈 loc[ ]: accesses rows and columns by label or condition.

🏳️‍🌈 iloc[ ]: Access data by row number.

🏳️‍🌈 merge(): Merge dataframes with common columns.

🏳️‍🌈 groupby(): Grouping for easier analysis.

🏳️‍🌈 pivot_table(): Summarize data in pivot table format.

🏳️‍🌈 to_csv(): Save data as a CSV file.

🏳️‍🌈 pd.concat(): Concatenate multiple dataframes in rows or columns.

🏳️‍🌈 pd.melt(): Convert wide format data to long format.

🏳️‍🌈 pd.pivot_table(): Create a pivot table with multiple levels.

🏳️‍🌈 pd.cut(): Split the data into specific intervals.

🏳️‍🌈 pd.qcut(): Sort data by percentage.

🏳️‍🌈 pd.merge(): Merge data in database style for advanced linking.

🏳️‍🌈 DataFrame.apply(): Apply a custom function to the data.

🏳️‍🌈 DataFrame.groupby(): Analyze grouped data.

🏳️‍🌈 DataFrame.drop_duplicates(): Drop duplicate rows.

🏳️‍🌈 DataFrame.to_excel(): Save data directly to Excel file.


┌ 🐼 Pandas Functions
└ 📄 PDF

#MachineLearning #DeepLearning #BigData #Datascience #ML #Pandas #DataVisualization #ArtificialInteligence #SoftwareEngineering #GenAI #deeplearning #ChatGPT #OpenAI #python #AI #keras #SQL #Statistics #LLMs #AIagents

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Regression & Classification Loss Functions

#MachineLearning #DeepLearning #BigData #Datascience #ML #Pandas #DataVisualization #ArtificialInteligence #SoftwareEngineering #GenAI #deeplearning #ChatGPT #OpenAI #python #AI #keras #SQL #Statistics #LLMs #AIagents

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Python Network Programming Cheat Sheet 🖥

#MachineLearning #DeepLearning #BigData #Datascience #ML #Pandas #DataVisualization #ArtificialInteligence #SoftwareEngineering #GenAI #deeplearning #ChatGPT #OpenAI #python #AI #keras #SQL #Statistics #LLMs #AIagents

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Git commands basics

#MachineLearning #DeepLearning #BigData #Datascience #ML #Pandas #DataVisualization #ArtificialInteligence #SoftwareEngineering #GenAI #deeplearning #ChatGPT #OpenAI #python #AI #keras #SQL #Statistics #LLMs #AIagents

http://t.me/codeprogrammer ✅

👩‍💻 Python Developer Roadmap is a guide for aspiring Python developers that helps structure and plan their learning and career development!

🌟 It provides a step-by-step plan that covers key aspects of Python development, from basic knowledge and syntax to more advanced topics such as databases, web development, testing, machine learning, and microservices development.

🔐 License: MIT

🖥 Github

https://t.me/CodeProgrammer ✅

🎯 All free IBM courses for data science
✅ Along with a certificate of completion


1️⃣ Data Science Fundamentals Course

✏️ Learn basic data science concepts such as analysis, modeling, and its real-world applications.
✂️✂️✂️✂️✂️

2️⃣ Applied Data Science Course with Python

✏️ Learn how to use Python for data analysis, modeling, and practical projects.
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3️⃣ Data Analysis Course with Python

✏️ Data analysis skills using Python libraries such as Pandas and NumPy.
✂️✂️✂️✂️✂️

4️⃣ Data visualization course with Python

✏️ Learn to create advanced charts with tools like Matplotlib and Seaborn.
✂️✂️✂️✂️✂️

5️⃣ Applied Data Science Course with R

✏️ Using the R language to analyze data and implement data science projects.
✂️✂️✂️✂️✂️

6️⃣ Data visualization course with R

✏️ Learn how to create professional charts and visualize data with tools like ggplot2.
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7️⃣ Big Data Fundamentals Course

✏️ Learn the fundamentals of big data and related technologies such as Hadoop and Spark.
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8️⃣ Scala Programming Course for Data Science

✏️ Familiarity with the Scala language and its use in data analysis projects.
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9️⃣ Data Science for Business Course

✏️ Learn how to use data to improve business decisions.
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1️⃣ Deep Learning Fundamentals Course

✏️ Familiarity with the basics of deep learning and the concepts of neural networks.
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1️⃣ Deep Learning Course with TensorFlow

✏️ Working with TensorFlow to build and train deep learning models.

https://t.me/CodeProgrammer ✅

✅ A comprehensive playlist to step into and master the world of machine learning and data science!


1️⃣ Data Science Principles:

😉 Essential Mathematics for Machine Learning: Link
😉 Overview and commonly used terms: Link
😉 Current interview trends: Link
😉 Linear Regression Guide: Link
😉 Logistic Regression Playlist: Link
😉 Classification criteria: Link
😉 Simple Bayes Classifier: Link
😉 Types of variables: Link
😉 Dimension reduction: Link
😉 Entropy, mutual entropy, KL divergence: link
😉 Dynamic Pricing Overview: Link


2️⃣ Building recommender systems:

😉 Netflix Calibrated Recommendations: Link
😉 Netflix Integrated Recommendation Model: Link
😉 The Evolution of Recommender Systems: Link
😉 Embedding tutorial: Link
😉 Annoy library for approximate nearest neighbor: link
😉 Reducer product for ANN: Link
😉 Model-based account recommendations: Link
😉 PID controller for diversity: link
😉 Instagram Recommender System: Link
😉 LinkedIn CTR Modeling: Link
😉 Meituan's two-tower recommendation model: Link
😉 Scalable Two Tower Model Question-Item: Link
😉 Twitter Recommender Algorithm: Link
😉 eBay language model for recommender system: link
😉 Overcoming biases for recommender systems: Link


3️⃣ Advanced Model Techniques and Applications:

😉 Importance of Model Calibration: Link
😉 Detect and monitor data changes: Link
😉 Neural Networks Training: Link
😉 Analytics-based advertising with Pinterest: Link
😉 Using Pre-trained Bert: Link
😉 Model Compression with Knowledge Distillation: Link
😉 Multi-Armed Bandit Strategies: Link


4️⃣ The world of large language models (LLMs):

😉 Conversational AI: Link
😉 The dual nature of conversational language models: link
😉 Frontier Developments in LLM: Link
😉 Improving the performance of open source LLMs: Link
😉 Building artificial intelligence in Shah Rukh Khan style: Link

📂 Tags: #DataScience #Python #ML #AI #LLM #BIGDATA #Courses #Pandas

http://t.me/codeprogrammer ⭐️

Data Visualization Cheat sheets and Resources

Corpus of 32 DV cheat sheets, 32 DV charts and 7 recommended DV books

📂 Tags: #DataScience #Python #ML #AI #LLM #BIGDATA #Courses #Pandas #DV

http://t.me/codeprogrammer ⭐️

IP Address Information using Python 🖥

📂 Tags: #DataScience #Python #ML #AI #LLM #BIGDATA #Courses #Pandas #DV

http://t.me/codeprogrammer ⭐️

🚀 Free Python Course with Certificate🚀

Unlock the world of coding with our
Python Fundamentals for Beginners course—completely FREE! 🚀 Whether you're new to programming or want to brush up on your skills, this course has everything you need to get started.

Why Choose This Course?
💡 100% FREE—No hidden fees
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💡 Practical, hands-on learning with real examples

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📂 Tags: #DataScience #Python #ML #AI #LLM #BIGDATA #Courses #Pandas #DV

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Python Cheatsheets ⭐️

Don't forget to React ❤️ to this msg if you want more content Like this 👍

📂 Tags: #DataScience #Python #ML #AI #LLM #BIGDATA #Courses #Pandas #DV

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Python Notes ⭐️

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📂 Tags: #DataScience #Python #ML #AI #LLM #BIGDATA #Courses #Pandas #DV

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🎥 Free course "Computational Thinking and Data Science"
📊 MIT University

👨🏻‍💻 One of the best resources I've found for learning computational thinking and data science is this free course from MIT. It covers concepts like data analysis, computational modeling, and using algorithms to solve complex problems. I've included the links to the slides and videos from the course below:👇

📄 Slides link: Lecture Slides and Files

📹 Video links: Lecture Videos

📂 Tags: #DataScience #Python #ML #AI #LLM #BIGDATA #Courses #Pandas #DV #MIT

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👨🏻‍💻 One of the most popular GitHub repositories for "learning and using algorithms in Python" is The Algorithms - Python repo with 196K stars.

✏️ It has a lot of organized and categorized code that you can use to find, read, and run different algorithms. Everything you can think of is here; from simple algorithms like sorting to advanced algorithms for machine learning, artificial intelligence, neural networks, and more.

✅ Why should we use it?

🔢 For learning: If you're looking to learn algorithms in action, this is great.

🔢 For practice: You can take the codes, run them, and modify them to better understand.

🔢 For projects : You can even use the codes here in real-life or academic projects.

🔢 For interviews: If you're preparing for data science interviews, this is full of practical algorithms.


┌ 🏳️‍🌈 The Algorithms - Python
└ 🐱 GitHub-Repos

📂 Tags: #DataScience #Python #ML #AI #LLM #BIGDATA #Courses #Pandas #DV #MIT

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15 ways to optimize neural network training

📂 Tags: #DataScience #Python #ML #AI #LLM #BIGDATA #Courses #Pandas #DV #MIT

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GANs clearly explained with visuals

This website provides a clear explanation, Try it out yourself: poloclub.github.io/ganlab/

📂 Tags: #DataScience #Python #ML #AI #LLM #Courses #Pandas #DV #GAN

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🪙 Everything you need to get started in machine learning.

Start with Python, explore scikit-learn, and neural networks using PyTorch. Perfect for beginners—get the skills you need to advance your career in just a few hours.

Start for free ▶️ ow.ly/HBtl50UtwCA

📂 Tags: #DataScience #Python #ML #AI #LLM #Courses #Pandas #DV #GAN

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Arcade Academy - Learn Python 🖥

📖 Book

📂 Tags: #DataScience #Python #ML #AI #LLM #Courses #Pandas #DV #GAN

http://t.me/codeprogrammer ⭐️