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Top 18 Machine Learning tools for developer in 2023.

See details of features and pricing of Machine Learning developer tools. We're comparing best apps, libraries or tools for Machine Learning such as DeepAI, lobe.ai, Levity AI, Liner, Nuclia, Paperspace Gradient, Kaggle, Google Colab, Weblab, Deepnote, MindsDB, SERP AI, Jupyter Notebook, Noteable, CoCalc, NextJournal, Apache Zeppelin, Hex to help you find your next Machine Learning tool. .

If you know the best tool for Machine Learning that not listed here,
please consider to submit it here.

🤙🏽 Skip to product:

  1. DeepAI
  2. lobe.ai
  3. Levity AI
  4. Liner
  5. Nuclia
  6. Paperspace Gradient
  7. Kaggle
  8. Google Colab
  9. Weblab
  10. Deepnote
  11. MindsDB
  12. SERP AI
  13. Jupyter Notebook
  14. Noteable
  15. CoCalc
  16. NextJournal
  17. Apache Zeppelin
  18. Hex

1. DeepAI

logo DeepAI

DeepAI

The most popular research, guides, news and more in artificial intelligence


🛠 DeepAI's Features

What can developer do with DeepAI

Zendo

DeepAI's agent for visual tasks

Research

Discover the latest A.I. research

Definitions

Learn top data science & A.I. terms

News

Track the latest news coverage in A.I.

Datasets

Discover datasets for A.I. & data science


2. lobe.ai

logo lobe.ai

lobe.ai

Download the free, easy to use app that helps you train custom machine learning models and ship them in your app.


🛠 lobe.ai's Features

What can developer do with lobe.ai

Easy to Use

Designed to be easy enough for anyone to use. No code or experience required.

Free and Private

Train for free on your own computer without uploading your data to the cloud.

Export Anywhere

Available for Mac and Windows. Export your model and ship it on any platform you choose


3. Levity AI

logo Levity AI

Levity AI

Train your own AI on documents, images, or text data to perform daily, repetitive tasks so your team can reach the next level of productivity. No code required.


🛠 Levity AI's Features

What can developer do with Levity AI

Upload training data

Feed Levity with images, PDFs or text data and the categories to learn from.

Train your AI Block

Your custom AI block learns from your data with the click of a button.

Connect your AI Block

Connect Levity to your apps and automate your workflow end-to-end.


💰 Levity AI's Pricing

How much does Levity AI cost?

Startup $ 200/month

  • For small teams that want to automate a few simple workflows with AI.
  • 5,000 actions per month
  • 10 AI trainings per month
  • Unlimited AI Blocks
  • Unlimited Flows
  • Chat support

Business $500/month

For businesses that want to use AI to transform their processes and reach next level productivity.

  • 50,000 actions per month
  • 50 AI trainings per month
  • Unlimited AI Blocks
  • Unlimited Flows
  • Chat & phone support

Enterprise Custom

  • For companies with large volumes that need additional control, security and support
  • Unlimited actions
  • Unlimited AI trainings
  • Role-based access control
  • Audit logs
  • SAML-based SSO
  • Dedicated success manager

4. Liner

logo Liner

Liner

Liner is a free tool which lets you build and deploy machine learning applications within minutes. No coding or expertise in machine learning required.


🛠 Liner's Features

What can developer do with Liner

1 Import your data

Import your data and view it within Liner. You can also use a pre-labeled dataset.

2 Start training

With a press of a button Liner will automatically choose an appropriate model and train it.

3 Deploy your model

Export your model to a variety of platforms and easily integrate it with your application.


💰 Liner's Pricing

How much does Liner cost?

Liner is completely free to use! Liner is a free and easy-to-use tool that runs on both Windows and Mac.

5. Nuclia

logo Nuclia

Nuclia

The API to make the unsearchable, searchable. Build and optimized search-experience using the low-code Nuclia search engine API to get multi-language semantic results, specific paragraphs, text or relations.


🛠 Nuclia's Features

What can developer do with Nuclia

How does Nuclia bring search to the next level?

  • Nuclia’s semantic AI is able to “understand” what your users are looking for.
  • Nuclia’s AI replaces the complexity of rule-based searching and offers a better experience to users.
  • Nuclia offers better and more relevant results to users by mixing in a “single” result, keyword results and semantic results.
  • If a user doesn’t know the exact keyword to search for, they can just describe what they want, and get optimized results.

6. Paperspace Gradient

logo Paperspace Gradient

Paperspace Gradient

From exploration to production, Gradient enables individuals and teams to quickly develop, track, and collaborate on Deep Learning models.


🛠 Paperspace Gradient's Features

What can developer do with Paperspace Gradient

  • Faster and persistent storage (no more reinstalling libraries and re-uploading files every time you start your notebook!).
  • Sessions are guaranteed, so you’re not at risk of having your instance shut down in the middle of your work. You don't need to be connected the entire time, either; start your training, log out, come back later, and your session will be right where you left off.
  • Pre-configured containers and templates. You can choose between different popular environments with all dependencies preinstalled (e.g. PyTorch, TensorFlow, or Data Science Stack), or use your own custom container. There's also an ML Showcase which includes sample projects you can fork (for free) and run on your own account.
  • A public datasets repository including a large selection of popular datasets mounted to each notebook and freely available for use.
  • The ability to easily scale up to add more storage and higher-end dedicated GPUs for the same environment, as you need.
  • Integrated features for a full ML pipeline, such as 1-click deployments and version control
  • A responsive and helpful support team.

💰 Paperspace Gradient's Pricing

How much does Paperspace Gradient cost?

FREE

For beginners, explorers, & adventurous learners

  • 1 member
  • Public projects
  • 5GB storage
  • Basic instances

PRO INDIVIDUAL ($8/month)

For ML engineers, data scientists, & researchers

  • 1 member
  • Private projects
  • 15GB storage
  • Mid-range instances
  • Faster free GPUs 🚀

PRO TEAM ($12/user/month )

For ML engineers, data scientists, and researchers

  • 2 members max
  • Private projects
  • 15GB storage
  • Mid-range instances
  • Collaboration

GROWTH ($39/user/month)

For teams, research groups, & startups

  • 5 members max
  • Private projects
  • 50GB storage
  • High-end instances
  • Expert Support

ENTERPRISE (Contact Sales)

For professional teams building applications at scale

  • Unlimited members
  • Private clusters
  • Unlimited storage
  • Solutions engineering
  • Premium support
  • SSO

7. Kaggle

logo Kaggle

Kaggle

Kaggle is the world’s largest data science community with powerful tools and resources to help you achieve your data science goals.


🛠 Kaggle's Features

What can developer do with Kaggle

Kaggle offers a no-setup, customizable, Jupyter Notebooks environment. Access GPUs at no cost to you and a huge repository of community published data & code. Inside Kaggle you’ll find all the code & data you need to do your data science work. Use over 50,000 public datasets and 400,000 public notebooks to conquer any analysis in no time.


💰 Kaggle's Pricing

How much does Kaggle cost?

Everything on Kaggle is completely free: courses, certificates obtained from courses, datasets, participation in competitions, discussion sections, etc.

8. Google Colab

logo Google Colab

Google Colab

Colab is a free Jupyter notebook environment that runs entirely in the cloud.


🛠 Google Colab's Features

What can developer do with Google Colab

Colab, or ‘Colaboratory’, allows you to write and execute Python in your browser, with

  • Zero configuration required
  • Access to GPUs free of charge
  • Easy sharing

Whether you're a student, a data scientist or an AI researcher, Colab can make your work easier.


💰 Google Colab's Pricing

How much does Google Colab cost?

Free

$0/mo

  • Free instances only
  • Notebooks are public
  • Limit 1 concurrent notebook
  • Limit 12 hours max per session
  • 5GB persistent storage
  • Free M4000 GPU

Pro (Individual)

$8/mo

  • Free and Paid instances
  • Private notebooks
  • Limit 3 concurrent notebooks
  • Unlimited session length
  • 15GB persistent storage
  • Free M4000 GPU
  • Free P4000 GPU
  • Free RTX4000 GPU
  • Free P5000 GPU
  • Free RTX5000 GPU
  • Free A4000 GPU

Pro (Team)

$12/mo

  • Free and Paid instances
  • Private notebooks
  • Limit 3 concurrent notebooks
  • Unlimited session length
  • 15GB persistent storage
  • Free M4000 GPU
  • Free P4000 GPU
  • Free RTX4000 GPU
  • Free P5000 GPU
  • Free RTX5000 GPU
  • Free A4000 GPU

Growth (Team)

$39/user/mo

  • Free and Paid instances
  • Private notebooks
  • Limit 10 concurrent notebooks
  • Unlimited session length
  • 50GB persistent storage
  • Free M4000 GPU
  • Free P4000 GPU
  • Free RTX4000 GPU
  • Free P5000 GPU
  • Free RTX5000 GPU
  • Free A4000 GPU
  • Free A5000 GPU
  • Free A6000 GPU

9. Weblab

logo Weblab

Weblab

Weblab lets you write and evaluate Javascript in an interactive notebook. It gives you a great environment to build Machine learning and Data Science applications.


🛠 Weblab's Features

What can developer do with Weblab

Interactive

Evaluate code cells and immediately see the output.

Compatible

Weblab supports the Jupyter-Notebook format.

Javascript

Harness Javascript libraries for machine learning and data science.


💰 Weblab's Pricing

How much does Weblab cost?

Free

10. Deepnote

logo Deepnote

Deepnote

Managed notebooks for data scientists and researchers.


🛠 Deepnote's Features

What can developer do with Deepnote

Collaborative by default

We built collaboration into Deepnote by default because data teams don’t work alone. Deepnote runs seamlessly in the cloud, making environment management a non-issue. And sharing work is as easy as sending a link (think Google Docs).

Integrates with your data stack

Deepnote works with the tools and frameworks you’re already using and familiar with. Use Python, SQL, R, TensorFlow, PyTorch, and any of your favorite languages or frameworks. Easily connect to data sources with dozens of native integrations.

Built to give you superpowers

We created Deepnote to make you more productive. Whether you work in a team or by yourself, Deepnote helps you clean your data, write complex queries, build predictive models, and ship beautiful apps.

Enterprise-grade security

Secure by default by following the industry best practices like fine-grained access controls, SSO support or on-premise deployments.

  • Encrypted data and credentials
  • SOC2 and PCI compliant
  • Audit logs
  • Notebook history

💰 Deepnote's Pricing

How much does Deepnote cost?

Free

For individuals who want to experience the full power of Deepnote. $0/editor/month

  • Up to 3 editors
  • Up to 5 projects
  • 7 day revision history

Team

For data teams who need to collaborate and share their work. $39/editor/month

  • Up to 3 editors
  • Up to 5 projects
  • 7 day revision history
  • Unlimited team members & projects
  • More powerful hardware
  • Premium integrations (Snowflake, SQL Server, BigQuery, Redshift, and more)
  • 30 day revision history

Enterprise

For organizations with more computation and security needs. Custom

  • Up to 3 editors
  • Up to 5 projects
  • 7 day revision history
  • Unlimited team members & projects
  • More powerful hardware
  • Premium integrations (Snowflake, SQL Server, BigQuery, Redshift, and more)
  • 30 day revision history
  • Volume compute discounts
  • Okta SSO
  • Unlimited revision history
  • Dedicated success manager
  • Custom contract & invoice

11. MindsDB

logo MindsDB

MindsDB

Make predictions from tables inside your database, then visualize them in your BI tool or App, all using standard SQL.


🛠 MindsDB's Features

What can developer do with MindsDB

Build ML powered applications fast.

Merge the capabilities of your database with popular ML frameworks to radically simplify the process of applying machine learning to applications.

Built for the modern day Full-Stack Developer.

AI Tables behave just like standard database tables. Using familiar SQL statements – time series, regression, and classification models can be trained and deployed automatically. Power simple or complex ML workflows without the burdensome overhead of traditional ML.

Over 70 integrations that seamlessly work with your tech stack


💰 MindsDB's Pricing

How much does MindsDB cost?

Run the most stable version of MindsDB on AWS

$0.70 /hr What’s included beyond the open source edition:

Rapid setup

Start solving your business problems with ML, without hours spent configuring MindsDB and instances

Certified Integrations

Integrations developed, tested and maintained by MindsDB – cuts down the time spent debugging and troubleshooting

Dedicated support

Have your ML questions answered by our ML engineers in a dedicated Slack channel

Option to Upload a Custom Model

Bring a custom/pre-trained model to MindsDB and hook it up directly to the database. No complicated data pipelines or model serving architectures required

12. SERP AI

logo SERP AI

SERP AI

Artificial Intelligence for the greatest good, for the greatest number.


🛠 SERP AI's Features

What can developer do with SERP AI

  • Database of tools
  • AI/ML papers, datasets, models
  • News
  • Tutorials

💰 SERP AI's Pricing

How much does SERP AI cost?

  • Free

13. Jupyter Notebook

logo Jupyter Notebook

Jupyter Notebook

The Jupyter Notebook is a web-based interactive computing platform. The notebook combines live code, equations, narrative text, visualizations, interactive dashboards and other media.


🛠 Jupyter Notebook's Features

What can developer do with Jupyter Notebook

Language of choice

Jupyter supports over 40 programming languages, including Python, R, Julia, and Scala.

Share notebooks

Notebooks can be shared with others using email, Dropbox, GitHub and the Jupyter Notebook Viewer.

Interactive output

Your code can produce rich, interactive output: HTML, images, videos, LaTeX, and custom MIME types.

Big data integration

Leverage big data tools, such as Apache Spark, from Python, R, and Scala. Explore that same data with pandas, scikit-learn, ggplot2, and TensorFlow.


💰 Jupyter Notebook's Pricing

How much does Jupyter Notebook cost?

Open source and free

14. Noteable

logo Noteable

Noteable

SQL, Python, R, and No-code Data Visualization in one single collaborative data notebook platform built around jupyter notebooks. EDA & ETL Made Easy.


🛠 Noteable's Features

What can developer do with Noteable

Ease Access to Data & Compute

Connect to Anything

Seamlessly connect to your data no matter where it's stored, featuring native integrations with BigQuery, Snowflake, Databricks, and more. Plus easily and securely connect to external APIs.

Fatest Way to Insight

Native SQL support within a Python notebook gives you the flexibility to work with data the way you want without sacrificing collaboration.

Resource Management

Configure your own compute and share credentials and important data across teams

Work with data the way you want

No-Code Visualizations

No matter your code level, turn your data into stories with the largest library of built-in visualizations.

Share and Comment

Go deeper on collaboration by commenting on anything - all the way down to specific data points.

Live Collaboration

Work together and simultaneously from anywhere without worrying about losing your work.

Boost your ML, Dashboard, and Data Pipelines

Scheduling

Schedule notebooks to run automatically, even within your existing production pipelines.

Git Support

Noteable allows you to work from a clone of a remote Git repository.

Data Apps & Dashboard

Share your data's story with easy-to-build, easy-to-share, and customizable published notebooks.


💰 Noteable's Pricing

How much does Noteable cost?

Screenshot 2023-06-03 at 20.22.44.png

15. CoCalc

logo CoCalc

CoCalc

Improve your research, teaching, and publishing using realtime collaborative Jupyter notebooks.


🛠 CoCalc's Features

What can developer do with CoCalc

CoCalc provides an interactive web-based Jupyter notebook that supports many popular kernels (such as Python, Julia, R, and SageMath) and allows for simultaneous collaboration between project members with seamless synchronization.

Our notebooks also include a unique feature called TimeTravel which enables users to recover their previous work and directly visualize what other collaborators have contributed to the file.


💰 CoCalc's Pricing

How much does CoCalc cost?

Screenshot 2023-06-03 at 20.28.46.png

16. NextJournal

logo NextJournal

NextJournal

Improve your workflow with polyglot notebooks, automatic versioning and real-time collaboration.


🛠 NextJournal's Features

What can developer do with NextJournal

Work together in real-time

Groups & Collaborators

Create public or private groups to work with your collaborators under a shared profile or invite them on a per-notebook basis. Secrets can be shared among collaborators.

Real-Time Sync

All edits to a Nextjournal notebook are commit-less and synchronized in real-time among connected clients. This allows editing of a notebook by multiple authors at the same time.

Rapid and full reusability

Remix entire notebooks

Enabled by immutability, “Remix” allows you to quickly build off a copy of any previously published notebook, including all of its dependencies.

Create, share and reuse Docker images

The entire file system can be published as Docker image with a single click. These images can be pulled to run locally or reused in other Nextjournal notebooks.

Polyglot Notebooks

In Nextjournal, you can use multiple programming language runtimes together in a single notebook. Values can be exchanged between runtimes using files.

Easy-to-manage runtime states

Runtimes are Docker containers that are orchestrated by a separate “Runner” application. This allow resetting an individual runtimes state without affecting other runtimes.

Arbitrary installations

Nextjournal can install anything as long as a runtime offers Bash. Environment variables can be set for each runtime through a UI.

Default environments

We offer default environments for various languages and use cases that come pre-populated with libraries for plotting, number crunching and more.

Automatic Provisioning & Shutdown

Every notebook that is run, gets its own compute instance provisioned automatically. We keep a pool of small runners around with 4GB of RAM per instance that will boot instantly. Larger instances are available on-demand. When your computation is done, we shut it down automatically to save costs on idling machines.

Full GPU support

Currently, we have full support for up to 8 NVIDIA Tesla K80, P100 or P100 Workstation GPUs per runtime with minimal setup necessary.

Data & Secrets Management

Connect your data

Besides uploading files, Nextjournal notebooks can bring in private data from S3 and Google Cloud Storage. You can also clone private GitHub repositories or import images from Docker Hub.

Secrets management

Secrets can be added to your account’s private secrets storage that lives outside notebooks and computational environments. Secrets are stored securely in Vault and can only be read by your profile.


💰 NextJournal's Pricing

How much does NextJournal cost?

Personal

Screenshot 2023-06-03 at 20.37.21.png

Teams

Screenshot 2023-06-03 at 20.37.37.png

17. Apache Zeppelin

logo Apache Zeppelin

Apache Zeppelin

Web-based notebook that enables data-driven, interactive data analytics and collaborative documents with SQL, Scala, Python, R and more.


🛠 Apache Zeppelin's Features

What can developer do with Apache Zeppelin

Zeppelin SDK

Not only you can use Zeppelin as interactive notebook, you can also use it as JobServer via Zeppelin SDK (client api & session api)

Spark Interpreter Improved

Spark interpreter provides comparable Python & R user experience like Jupyter Notebook. For the details, click here.

Flink Interpreter Improved

Flink interpreter is refactored, supports Scala, Python & SQL. Flink 1.10 and afterwards (Scala 2.11 & 2.12) are all supported. For the details, click here.

Yarn Interpreter Mode

You can run interpreter in yarn cluster, e.g. you can run Python interpreter in yarn and R interpreter in yarn.

Inline Configuration

Generic ConfInterpreter provide a way configure interpreter inside each note.

Interpreter Lifecycle Management

Interpreter lifecycle manager automatically terminate interpreter process on idle timeout. So resources are released when they're not in use. See here for more details.


💰 Apache Zeppelin's Pricing

How much does Apache Zeppelin cost?

Open source

18. Hex

logo Hex

Hex

Hex is a modern data platform for data science and analytics. Collaborative notebooks, beautiful data apps and enterprise-grade security.


🛠 Hex's Features

What can developer do with Hex

Mix and match SQL, Python, and no-code

Use the right tool for the right job, in Hex’s beautiful, polyglot notebooks.

Magic AI, built right in

Generate, edit, debug, and explain your code with a built-in AI assistant.

Beautiful, interactive visualizations

Visualize datasets of any size using charts, formattable tables, pivots, maps, and more.

Governed metrics, unlimited possibility

Explore metrics from dbt’s Semantic Layer, without writing code. Plus, a first-class docs integration.


💰 Hex's Pricing

How much does Hex cost?

Screenshot 2023-06-03 at 20.48.42.png

👋🏽 About Machine Learning

Machine learning is a type of artificial intelligence (AI) that allows computer systems to learn and improve from experience without being explicitly programmed. It involves the use of algorithms and statistical models to enable a system to improve its performance on a specific task over time.

In machine learning, a system is typically trained on a large dataset, and the algorithms and models are used to identify patterns and relationships in the data. The system can then use this knowledge to make predictions or decisions about new data. For example, a machine learning system might be trained on a dataset of images of animals, and it would use this training to identify new images of animals.

Machine learning has many applications, such as in image and speech recognition, natural language processing, and predictive analytics. It is an important area of study in computer science and has the potential to revolutionize many fields.

👋🏽 What is this page?

"What is the best Machine Learning tool for developer? " Hope this page answering your question. This is a comparison page of recommended Machine Learning coding tools, for developer by developer. Find your next top Machine Learning alternative programming tools here. We list features and pricing with hope this resources can help you decide which Machine Learning tools you need and best for your next project.

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