streamlit
Streamlit β A faster way to build and share data apps.
Creator: Streamlit
Stars βοΈ: 35.4k
Forked By: 3.1k
https://github.com/streamlit/streamlit
#datascience
ββββββββββββββ
Join @datascience_bds for more cool repositories.
*This channel belongs to @bigdataspecialist group
Streamlit β A faster way to build and share data apps.
Creator: Streamlit
Stars βοΈ: 35.4k
Forked By: 3.1k
https://github.com/streamlit/streamlit
#datascience
ββββββββββββββ
Join @datascience_bds for more cool repositories.
*This channel belongs to @bigdataspecialist group
GitHub
GitHub - streamlit/streamlit: Streamlit β A faster way to build and share data apps.
Streamlit β A faster way to build and share data apps. - streamlit/streamlit
π2
Essential Machine Learning Algorithms for Data Scientists
Master essential machine learning algorithms and elevate your data science skills
Rating βοΈ: 4.6 out 5
Students π¨βπ : 791
Duration β° : 43min of on-demand video
Created by π¨βπ«: Arunkumar Krishnan
π Course Link
#ml #algorithm
ββββββββββββββ
πJoin @datascience_bds for moreπ
Master essential machine learning algorithms and elevate your data science skills
Rating βοΈ: 4.6 out 5
Students π¨βπ : 791
Duration β° : 43min of on-demand video
Created by π¨βπ«: Arunkumar Krishnan
π Course Link
#ml #algorithm
ββββββββββββββ
πJoin @datascience_bds for moreπ
Udemy
Free Data Science Tutorial - Essential Machine Learning Algorithms for Data Scientists
Master essential machine learning algorithms and elevate your data science skills - Free Course
π3
Forecasting vs. Predictive Analytics: The Obama Example
Analytics can influence elections, not just predict them. This article explores how the Obama campaign used predictive analytics to outmaneuver traditional forecasting.
Forecasting vs. Predictive Analytics
Nate Silverβs forecasting predicted state outcomes, while Obamaβs team used predictive analytics to score individual voters, targeting those most likely to be persuaded.
Impact of Predictive Analytics
The Obama campaign optimized interactions, avoiding βdo-not-disturbβ voters and improving ad spending effectiveness by 18%.
Conclusion
Predictive analytics enables organizations to shape outcomes through personalized insights, distinguishing it from forecastingβs broad predictions.
Analytics can influence elections, not just predict them. This article explores how the Obama campaign used predictive analytics to outmaneuver traditional forecasting.
Forecasting vs. Predictive Analytics
Nate Silverβs forecasting predicted state outcomes, while Obamaβs team used predictive analytics to score individual voters, targeting those most likely to be persuaded.
Impact of Predictive Analytics
The Obama campaign optimized interactions, avoiding βdo-not-disturbβ voters and improving ad spending effectiveness by 18%.
Conclusion
Predictive analytics enables organizations to shape outcomes through personalized insights, distinguishing it from forecastingβs broad predictions.
π5β€3
macos
OSX (macOS) inside a Docker container.
Creator: Dockur
Stars βοΈ: 5.2k
Forked By: 185
https://github.com/dockur/macos
#datascience
ββββββββββββββ
Join @datascience_bds for more cool repositories.
*This channel belongs to @bigdataspecialist group
OSX (macOS) inside a Docker container.
Creator: Dockur
Stars βοΈ: 5.2k
Forked By: 185
https://github.com/dockur/macos
#datascience
ββββββββββββββ
Join @datascience_bds for more cool repositories.
*This channel belongs to @bigdataspecialist group
GitHub
GitHub - dockur/macos: MacOS inside a Docker container.
MacOS inside a Docker container. Contribute to dockur/macos development by creating an account on GitHub.
π1
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 βοΈ: 4.3 out 5
Students π¨βπ : 4865
Duration β° : 5.5 hours on-demand video
Created by π¨βπ«: Sayman Creative Institute
π COURSE LINK
β οΈ Its free for first 1000 enrollments only!
#datascience #python
ββββββββββββββ
πJoin @datascience_bds for moreπ
Master Python for Data Science with Real-World Applications: Dive Deep into Data Analysis, Machine Learning
Rating βοΈ: 4.3 out 5
Students π¨βπ : 4865
Duration β° : 5.5 hours on-demand video
Created by π¨βπ«: Sayman Creative Institute
π COURSE LINK
β οΈ Its free for first 1000 enrollments only!
#datascience #python
ββββββββββββββ
πJoin @datascience_bds for moreπ
Udemy
Hands On Python Data Science - Data Science Bootcamp
<p>This comprehensive course is designed for both beginners and those looking to sharpen their data science skills. Through a step-by-step approach, youβll learn to harness Pythonβs powerful libraries like Pandas, NumPy, Matplotlib, and Scikit-Learn, enablingβ¦
β€6π2
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 βCompetitive Advantage: Creating and Sustaining Superior Performanceβ.
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.
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 βCompetitive Advantage: Creating and Sustaining Superior Performanceβ.
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.
π6