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Top 10 Data Libraries for Python
macos

OSX (macOS) inside a Docker container.

Creator: Dockur
Stars ⭐️: 5.2k
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https://github.com/dockur/macos

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Exploratory Data Analysis
The Data Science Process
Hands On Python Data Science - Data Science Bootcamp

Master Python for Data Science with Real-World Applications: Dive Deep into Data Analysis, Machine Learning

Rating ⭐️: 4.3 out 5
Students 👨‍🎓 : 4865
Duration : 5.5 hours on-demand video
Created by 👨‍🏫: Sayman Creative Institute

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Data Science for Value-Chain Management

How can you leverage data science to optimize operations and boost profitability?

Value Chain Management (VCM) refers to organizing activities that add value to the goods or services to achieve a competitive advantage in the marketplace.

This method helps organizations to effectively respond to market trends and improve efficiency to boost profitability.

We quickly delve into the fundamental components of Value Chain Management.

We will then explore four examples of data science applications to support strategic primary activities.

The value chain framework was originally introduced in Michael Porter's book “Competitive Advantage: Creating and Sustaining Superior Performance”.

This revolutionized how businesses perceive their operations by dissecting any business into a series of interconnected activities that contribute to creating and delivering value to customers.
Data Science Life Cycle
Top Machine Learning algorithms
🌳 What is a Decision Tree? 🌳

Imagine you're trying to figure out what to eat for dinner. 🍕🥗🍔 A decision tree is like a flowchart that helps you make choices based on yes/no questions:

Are you in the mood for something light?
Yes ➡️ Salad 🥗
No ➡️ Are you craving something cheesy?
Yes ➡️ Pizza 🍕
No ➡️ Burger 🍔

That's the essence of how decision trees work in machine learning!

🤖 In Machine Learning Terms:

Nodes: Questions (e.g., Is the price > $50?)
Branches: Possible answers (e.g., Yes/No)
Leaves: Final decisions or predictions (e.g., "Expensive" or "Affordable")

📊 They're used for tasks like:
Classifying emails as spam or not.
Predicting if a customer will buy a product.
Diagnosing diseases in healthcare.

🎯 Why are they Awesome?

Simple to understand (even for non-techies).
Visual and interpretable (you can see the logic behind predictions).
Great for small-to-medium datasets.

⚡️ Limitations:

They can "overfit" (become too specific).
Not the best for very large datasets or complex problems.

🛠 Pro Tip:
To handle overfitting, use Random Forests 🌲🌲 or Gradient Boosted Trees 🚀—advanced versions of decision trees.

What do you think about decision trees? Drop your 🌳 below if you love their simplicity!
Begin to Use Cloud Computing with Anaconda Cloud Notebook

Begin to use Cloud Computing and Anaconda Cloud Notebook with Python, Data Science and Machine Learning [2024]

Rating ⭐️: 4.9 out 5
Students 👨‍🎓 : 1,028
Duration : 40min on-demand video
Created by 👨‍🏫: Henrik Johansson

🔗 Course Link


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Big Data Pipeline Cheatsheet
Roadmap To Master Machine Learning
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Data Science

common data analysis and machine learning tasks using python

Creator: Ujjwal Karn
Stars ⭐️: 5.3k
Forked By: 1.5k
GithubRepo: https://github.com/ujjwalkarn/DataSciencePython


#datascience #python

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Python for Deep Learning: Build Neural Networks in Python

Complete Deep Learning Course to Master Data science, Tensorflow, Artificial Intelligence, and Neural Networks

Rating ⭐️: 4.2 out 5
Students 👨‍🎓 : 145651
Duration : 2 hours on-demand video
Created by 👨‍🏫: Meta Brains, school of AI

🔗 Course Link

⚠️ Its free for first 1000 enrollments only!


#python #deeplearning

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Forwarded from Data visualization
Proficiency in data science skills by job role
15 different Careers in AI
2025/06/30 14:31:59
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