Microsoft Office Excel VS Scikit-learn

Microsoft Office Excel Reviews

1. amna123    

   content writter at content arcade | 6 months ago
   Unleashing the Potential with Microsoft Office Excel

   A software program created by Microsoft that uses spreadsheets to organize numbers and data with formulas and functions. It is one of the best software for daily use Microsoft Office Excel has been an absolute game-changer for me in the realm of spreadsheet applications. Whether it's managing data, creating intricate formulas, or visualizing trends, Excel stands out as a powerhouse of functionality and efficiency.

   👍 Pros:    Database management

   👎 Cons:    Learning curve
2. Rory    

   Entrepreneur at Konstrukt Planeringsverktyg | over 3 years ago
   Everyone loves to hate it, but it's the best!

   What would we do without Excel!? Sure, the online version isn't as simple as Google Sheets, they could have chosen not to localise the function names, and it's always chaos trying to consolidate multiple budget or forecast files & templates, but aside from that it's everyone's favourite spreadsheet. What you can't do in Excel isn't worth doing. Even if there's often a better way...

3. Rosstaylor9855    

   over 3 years ago
   Reliable Software

   It is one of the best software for daily purpose.

Scikit-learn Reviews

Microsoft Office Excel mentions (0)

Scikit-learn mentions (27)

• Link Prediction With node2vec in Physics Collaboration Network

  Firstly, we need a connection to Memgraph so we can get edges, split them into two parts (train set and test set). For edge splitting, we will use scikit-learn. In order to make a connection towards Memgraph, we will use gqlalchemy. - Source: dev.to / 11 months ago

• WiFilter is a RaspAP install extended with a squidGuard proxy to filter adult content. Great solution for a family, schools and/or public access point

  The ML component is based on scikit-learn which differentiates it from purely list-based filters. It couples this with a full-featured wireless router (RaspAP) in a single device, so it fulfills the needs of a use case not entirely addressed by Pi-hole. Source: 12 months ago

• PSA: You don't need fancy stuff to do good work.

  Finally, when it comes to building models and making predictions, Python and R have a plethora of options available. Libraries like scikit-learn, statsmodels, and TensorFlowin Python, or caret, randomForest, and xgboostin R, provide powerful machine learning algorithms and statistical models that can be applied to a wide range of problems. What's more, these libraries are open-source and have extensive... Source: 12 months ago

• Help on using R for Machine Learning?

  Scikit-learn is a machine learning library that comes with a number of pre-built machine learning models, which can then be used as python wrappers. Source: about 1 year ago

• Machine learning with Julia - Solve Titanic competition on Kaggle and deploy trained AI model as a web service

  This is not a book, but only an article. That is why it can't cover everything and assumes that you already have some base knowledge to get the most from reading it. It is essential that you are familiar with Python machine learning and understand how to train machine learning models using Numpy, Pandas, SciKit-Learn and Matplotlib Python libraries. Also, I assume that you are familiar with machine learning... - Source: dev.to / about 1 year ago