Software Alternatives, Accelerators & Startups

Scikit-learn VS Talk to Books by Google

Compare Scikit-learn VS Talk to Books by Google and see what are their differences

Scikit-learn logo Scikit-learn

scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

Talk to Books by Google logo Talk to Books by Google

Browse passages from books using experimental AI
  • Scikit-learn Landing page
    Landing page //
    2022-05-06
  • Talk to Books by Google Landing page
    Landing page //
    2019-10-03

Scikit-learn videos

Learning Scikit-Learn (AI Adventures)

More videos:

  • Review - Python Machine Learning Review | Learn python for machine learning. Learn Scikit-learn.

Talk to Books by Google videos

No Talk to Books by Google videos yet. You could help us improve this page by suggesting one.

+ Add video

Category Popularity

0-100% (relative to Scikit-learn and Talk to Books by Google)
Data Science And Machine Learning
AI
0 0%
100% 100
Data Science Tools
100 100%
0% 0
Developer Tools
0 0%
100% 100

User comments

Share your experience with using Scikit-learn and Talk to Books by Google. For example, how are they different and which one is better?
Log in or Post with

Reviews

These are some of the external sources and on-site user reviews we've used to compare Scikit-learn and Talk to Books by Google

Scikit-learn Reviews

15 data science tools to consider using in 2021
Scikit-learn is an open source machine learning library for Python that's built on the SciPy and NumPy scientific computing libraries, plus Matplotlib for plotting data. It supports both supervised and unsupervised machine learning and includes numerous algorithms and models, called estimators in scikit-learn parlance. Additionally, it provides functionality for model...

Talk to Books by Google Reviews

We have no reviews of Talk to Books by Google yet.
Be the first one to post

Social recommendations and mentions

Based on our record, Scikit-learn should be more popular than Talk to Books by Google. It has been mentiond 28 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.

Scikit-learn mentions (28)

  • How to Build a Logistic Regression Model: A Spam-filter Tutorial
    Online Courses: Coursera: "Machine Learning" by Andrew Ng EdX: "Introduction to Machine Learning" by MIT Tutorials: Scikit-learn documentation: https://scikit-learn.org/ Kaggle Learn: https://www.kaggle.com/learn Books: "Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow" by Aurélien Géron "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani, and Jerome Friedman By... - Source: dev.to / 3 months ago
  • 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 / 12 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: about 1 year 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: about 1 year 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
View more

Talk to Books by Google mentions (9)

  • 🧰 AI Tools of the Day (6-14-23)
    Talk to Books is an AI product by Google that can be used to interact with the content written in books that are already published. Source: 12 months ago
  • ChatGPT is making all my code more efficient and allowing me to focus on broader concepts rather than finding the correct phrasing.
    You can also use Google's Talk to Books that uses a neural network to search them. It's very handy! Source: over 1 year ago
  • AI tools which can help you daily
    Talk to books (https://books.google.com/talktobooks) : With talktobooks, you can talk to a book like in the same way as we talk to humans. Source: over 1 year ago
  • Searching for Kasparov quote on the fight for truth in chess?
    While I couldn't find the quote you mentioned, you can try using Talk to Books, an AI where you ask a question and it shows a quote from a book. Source: over 1 year ago
  • Ask HN: What are the most interesting AI applications accessible to the layman?
    For example, projects such as https://books.google.com/talktobooks/ that allow people to experience AI without programming. - Source: Hacker News / over 1 year ago
View more

What are some alternatives?

When comparing Scikit-learn and Talk to Books by Google, you can also consider the following products

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

A.I. Experiments by Google - Explore machine learning by playing w/ pics, music, and more

OpenCV - OpenCV is the world's biggest computer vision library

Facebook.ai - Everything you need to take AI from research to production

NumPy - NumPy is the fundamental package for scientific computing with Python

Lobe - Visual tool for building custom deep learning models