Data Science and Machine Learning Platforms Resources
Articles, Glossary Terms, Discussions, and Reports to expand your knowledge on Data Science and Machine Learning Platforms
Resource pages are designed to give you a cross-section of information we have on specific categories. You'll find articles from our experts, feature definitions, discussions from users like you, and reports from industry data.
Data Science and Machine Learning Platforms Articles
Seq2Seq Models: How They Work and Why They Matter in AI
10 Best Data Labeling Software With G2 User Reviews
What Is Artificial Intelligence (AI)? Types, Definition And Examples
What Is Artificial General Intelligence (AGI)? The Future Is Here
2023 Trends in AI: Cheaper, Easier-to-Use AI to the Rescue
Barriers Toward Adopting AI and Analytics in the Supply Chain
The Importance of Data Quality and Commoditization of Algorithms
How to Choose a Data Science and Machine Learning Platform That’s Right For Your Business
Data Trends in 2022
How to Make Algorithms Which Explain Themselves
Artificial Intelligence in Healthcare: Benefits, Myths, and Limitations
The Role of Artificial Intelligence in Accounting
Tech Companies Bridging the Gap Between AI and Automation
How COVID-19 Is Impacting Data Professionals
True Data Protection Demands More Than Just Regulation
What Is the Future of Machine Learning? We Asked 5 Experts
Data Science and Machine Learning Platforms Glossary Terms
Data Science and Machine Learning Platforms Discussions
What is Google Cloud AI Platform used for?
<p>Hey G2! I want to start a community discussion about webinar software, more specifically, what are the most popular webinar software for enterprises? Do you have first-hand experience using these top-rated software systems in G2’s Webinar Software category:</p><p> That same spirit of shared experience applies here too. This time, I’m hoping to hear from developers, analysts, and product teams about which analytics tools have actually helped software development firms improve decision-making and product performance.</p><p>Here are some of the top-rated platforms from G2’s <a href="https://www.g2.com/categories/data-science-and-machine-learning-platforms" rel="noopener noreferrer" target="_blank">Data Science and Machine Learning Platforms</a> category:</p><p><a href="https://www.g2.com/products/google-vertex-ai/reviews" rel="noopener noreferrer" target="_blank"><strong>Vertex AI</strong></a></p><p> End-to-end ML platform from Google Cloud with strong integration into analytics tools like BigQuery. Good fit for product telemetry and predictive modeling in a cloud-native setup.</p><p><a href="https://www.g2.com/products/databricks-data-intelligence-platform/reviews" rel="noopener noreferrer" target="_blank"><strong>Databricks Data Intelligence Platform</strong></a></p><p> Combines analytics and machine learning in a unified environment. Popular among engineering-focused teams for centralizing logs, performance data, and usage metrics.</p><p><a href="https://www.g2.com/products/deepnote/reviews" rel="noopener noreferrer" target="_blank"><strong>Deepnote</strong></a></p><p> Collaborative notebooks designed for technical and non-technical teams to analyze data together. Useful for exploring product analytics, A/B tests, and customer behavior insights.</p><p><a href="https://www.g2.com/products/dataiku/reviews" rel="noopener noreferrer" target="_blank"><strong>Dataiku</strong></a></p><p> Offers both visual and code-based workflows. Helps connect devs, analysts, and product managers working across analytics and reporting use cases.</p><p><a href="https://www.g2.com/products/saturn-cloud-saturn-cloud/reviews" rel="noopener noreferrer" target="_blank"><strong>Saturn Cloud</strong></a></p><p> Cloud-based environment for Python with scalable compute. Designed for teams working with large datasets and advanced reporting pipelines.</p><p>What analytics platform has made the biggest impact for your software development team? Any takeaways or tools you would or wouldn’t recommend?</p>