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Tableau is recommended for data analysts, business intelligence professionals, and organizations that need to transform complex data into actionable insights. It is also suited for industries that rely on data-driven decision-making, such as finance, healthcare, and marketing, as well as any company looking to improve its data visualization capabilities.
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Iโve used Tableau to analyze and present data for business reporting, and its strength is clearly in visualization. Turning raw data into interactive dashboards is fast once you understand how the tool works, and the end results look polished and professional.
However, getting to that point isnโt instant. New users may struggle with calculations, data modeling, and performance tuning. Licensing costs are also high, which can be difficult to justify for smaller teams or individual users.
Tableau works best for organizations that rely heavily on data-driven decisions and can invest time and budget into analytics. Itโs not the easiest or cheapest option, but the output quality makes it worthwhile
Based on our record, Tableau should be more popular than micrograd. It has been mentiond 8 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I built the first version of DeepFork to understand micrograd โ Andrej Karpathy's 100-line autograd engine. Most people read micrograd for the aha moment. DeepFork turns that moment into an artifact. - Source: dev.to / about 2 months ago
Karpathy built a small project called micrograd. You can see the code here. This is made up of just a few simple lines of code, but it shows us how neural networks are built under the hood. In the video, he demonstrated how to build Micrograd and how it works step by step. - Source: dev.to / 2 months ago
It can happen like this: - write sleek operator-overloading-based code for simple mathematical operations on your custom pet algebra - decide that you want to turn it into an autograd library [0] - realise that you now need either `RefCell` for interior mutability, or arenas to save the computation graph and local gradients - realise that `RefCell` puts borrow checks on the runtime path and can panic if you get... - Source: Hacker News / 3 months ago
Good introduction! Building pytorch-lite using python and numpy is the way to go. Free book: https://zekcrates.quarto.pub/deep-learning-library/ Ml by hand : https://github.com/workofart/ml-by-hand Micrograd: https://github.com/karpathy/micrograd. - Source: Hacker News / 6 months ago
Let me be completely honest: I didn't invent anything here. This is Andrej Karpathy's brilliant micrograd ported to C++, nothing more, nothing less. But sometimes the best way to really understand something is to rebuild it in a different language, and that's exactly what I needed. - Source: dev.to / 11 months ago
Hey everyone, I'm interested in taking the Tableau Certified Data Analyst Exam Readiness course through tableau.com to prepare and get Tableau certified. I had some questions about the course, such as are the videos pre recorded or in person, do you have access to the material once the 90 days expire, and I was also wondering if anyone had input/advice for this course. Thanks! Source: about 3 years ago
Could anyone recommend what media I should approach to publish my work (internet or print). I could try the Tableau forum in tableau.com but it's not very active + Tableau may be unappreciative as my work overlaps with their (pricey) data management solution. Plus it needs to be some high visibility / reputable media to count for my career development. Any recommendations welcome thanks!!! Source: over 3 years ago
Tableau public: tableau.com. Big player but your data will be made public and not really user-friendly data model. Source: over 4 years ago
For example, we have a project to compare Tableau, Power BI, and InetSoft. The need for strong pagination-based email delivery eliminated Tableau. AWS's Linux instance is the targeted platform which makes Power BI less than ideal. Source: over 4 years ago
I just started learning Tableau because our dept is transitioning into Tableau from Power BI. Since I already have years of experience with Power BI I just went over their tutorials from tableau.com and got onboarded pretty quick. I'm still learning it but I'm at least able to build out reports and get things done. Its not too difficult to pickup one BI tool when you have experience with another. Source: over 4 years ago
tinygrad - This may not be the best deep learning framework, but it is a deep learning framework.
Microsoft Power BI - BI visualization and reporting for desktop, web or mobile
PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...
Looker - Looker makes it easy for analysts to create and curate custom data experiencesโso everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.
TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.
Qlik - Qlik offers an Active Intelligence platform, delivering end-to-end, real-time data integration and analytics cloud solutions to close the gaps between data, insights, and action.