Ratings based on the content, interactions and moderation score. We have analyzed the quality of these social groups, especially for Data Scientists on three parameters.
“No Road is long with Good Company.”- Turkish Proverb.
We cautiously select our friends, colleagues, and acquaintances because we know how important it is to be in a good company, and Social networking is no different.
We join groups on Facebook and LinkedIn; Pages on Twitter and Instagram to remain up to date with the emerging developments in Data Science, to ask questions related to our work, and to build connections.
We have analyzed the quality of these social groups, especially for Data Scientists on three parameters.
_1. Interaction: _How active the group members are in the group?
2. Content:_ What kind of content is exchanged in these groups?_
3. Moderation:_ Is the group free from potential spams and misleading advertisements and promotions?_
Data Set: *The data is collected from the last 50 posts from each of the groups on Facebook and LinkedIn. All the groups with more than 50K members on Facebook and LinkedIn are taken into consideration. This data is collected from 24th August 2020 to 28th August 2020. The data is hosted at https://www.kaggle.com/shrashtisinghal/data-science-social-groups-survey
Data Science Central
Data Mining, Statistics, Big Data, Data Visualization, AI, Machine Learning, and Data Science
Data Science — R & Python
Data Science World
Machine Learning and Data Science
Big Data ▶️ Data Science | Machine Learning | Deep Learning | Artificial Intelligence
Big Data, Machine Learning, Data Science, Artificial Intelligence, IoT & Blockchain
Beginning Data Science, Analytics, Machine Learning, Data Mining, R, Python
Data Science and Predictive Analytics News
Tableau Data Analysis Tips and Tricks. Master the one of the most powerful data analytics tool with some handy shortcut and tricks.
Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments. Our latest survey report suggests that as the overall Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments, data scientists and AI practitioners should be aware of the skills and tools that the broader community is working on. A good grip in these skills will further help data science enthusiasts to get the best jobs that various industries in their data science functions are offering.
Data science is omnipresent to advanced statistical and machine learning methods. For whatever length of time that there is data to analyse, the need to investigate is obvious.
In this article we are sharing a curated list of Top 5 Social Network App Development Companies which have extensive and years of experience in developing custom social network solutions.
Intro to Data Engineering for Data Scientists: An overview of data infrastructure which is frequently asked during interviews