Keras VS DeepKE

Let’s have a side-by-side comparison of Keras vs DeepKE to find out which one is better. This software comparison between Keras and DeepKE is based on genuine user reviews. Compare software prices, features, support, ease of use, and user reviews to make the best choice between these, and decide whether Keras or DeepKE fits your business.

Keras

Keras
Discover the power of Keras: an API designed for human beings. Reduce cognitive load, enhance speed, elegance, and deployability in Machine Learning apps.

DeepKE

DeepKE
DeepKE: Unified toolkit for high-precision Knowledge Extraction. Conquer low-resource, multimodal, & document-level data to build robust Knowledge Graphs.

Keras

Launched 2015-04
Pricing Model
Starting Price
Tech used Google Tag Manager,Amazon AWS CloudFront,Google Fonts,Bootstrap,Amazon AWS S3
Tag Software Development,Data Science,Code Generation

DeepKE

Launched
Pricing Model Free
Starting Price
Tech used
Tag

Keras Rank/Visit

Global Rank 147597
Country India
Month Visit 308086

Top 5 Countries

11.24%
7.35%
5.51%
5.37%
4.28%
India United States Germany Indonesia Brazil

Traffic Sources

2.21%
0.71%
0.1%
8%
58.5%
30.45%
social paidReferrals mail referrals search direct

DeepKE Rank/Visit

Global Rank
Country
Month Visit

Top 5 Countries

Traffic Sources

Estimated traffic data from Similarweb

What are some alternatives?

When comparing Keras and DeepKE, you can also consider the following products

Caffe - Caffe is a deep learning framework made with expression, speed, and modularity in mind.

DeepInfra - Run the top AI models using a simple API, pay per use. Low cost, scalable and production ready infrastructure.

KeaML Deployments - Streamline your AI development journey with KeaML - pre-configured environments, optimized resources, and collaborative tools. Experience seamless AI projects.

ktransformers - KTransformers, an open - source project by Tsinghua's KVCache.AI team and QuJing Tech, optimizes large - language model inference. It reduces hardware thresholds, runs 671B - parameter models on 24GB - VRAM single - GPUs, boosts inference speed (up to 286 tokens/s pre - processing, 14 tokens/s generation), and is suitable for personal, enterprise, and academic use.

More Alternatives