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Schwäbisch Gmünd, Germany
1-10 Employees
2020
Our mission is straightforward: we want to make our knowledge and experience in Artificial Intelligence (AI), Machine Learning and Deep Learning accessible to everyone. We are three guys from Germany with an academic background in mathematics. Introduction Microsoft Fabric is a powerful All-in-One Data Platform (SaaS) in the Azure Cloud that combines various Azure components to cover the fields of Data Integration, Data Engineering, Data Science and Business Intelligence. In order to explore and get to know Fabric, Microsoft offers a free trial. One powerful tool for achieving this is the use of type hints.
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DEEP LEARNING NERDS
... Our mission is to teach you the basics of Artificial Intelligence, Machine Learning, Deep Learning, Data Science and Python. Especially, we show you with awesome visualizations in several tutorials how to build, train, test and optimize aritficial neural networks. We from Deep Learning ...
Berlin, Germany
1-10 Employees
2019
The AIME A8004 is the ultimate multi-GPU server, optimized for maximum deep learning training, inference performance and for the highest demands in HPC computing: Dual EPYC Genoa CPUs, the fastest PCIe 5.0 bus speeds, up to 90 TB raided NVMe SSD storage and 100 GBE network connectivity. With the AIME A8000 you enter the Peta FLOPS HPC computing Deep Learning performance with up to eight GPUs or accelerators, dual EPYC CPU, 128 PCIe 4.0 lanes bus speeds and up to 100GB network connectivity. The Deep Learning server AIME A4004 is powered by the latest EPYC Genoa generation with up to four GPUs or accelerators packed into 2 height units, fastest PCIe 5.0 bus speeds and up to 100GB network connectivity. The predecessor of the AIME A4004 for EPYC Rome and Milan CPU generations, fast PCIe 4.0 bus speeds and up to 100GB network connectivity. The AIME G400 is the perfect workstation for Deep Learning development. Rent an AIME server, hosted in our AI cloud on a weekly or monthly basis as long as you need it. The AIME ML Container Manager makes life easier for developers so they do not have to worry about framework version installation issues. A multi GPU workhorse built to perform at your data center or co-location.
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AIME R400 - 4 GPU Rack Server | Deep Learning Workstations, Servers, GPU-Cloud Services | AIME
... 24/7 at your inhouse data center or co-location. Configurable with 4 high end deep learning GPUs (NVIDIA RTX 2080TI, Titan RTX, Tesla V100) which give you the fastest deep learning power available: upto 500 Trillion Tensor FLOPS of AI performance and 64 GB high speed GPU memory. ...
Davie, United States
1-10 Employees
2021
Applying world class sector-specific knowledge and experience to the solve the biggest problems in orthopedics. Building devices that create immediate value for clinicians and collect high quality data sets both inside and outside the operating theater. Staying at the forefront of advances in deep learning to provide unprecedented support for clinical decision making. “It is by logic that we prove, but by intuition that we discover.”. “Health care is my passion, but innovation is what inspires me.”.
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Deep Learning For Orthopedics
... Deep Learning For ...
Navi Mumbai, India
11-50 Employees
2018
Natural language processing (NLP) is the ability of a computer program to understand human language as it is spoken. NLP is a component of artificial intelligence (AI). Deep Learning (AI in general terms) is a trending topic in the tech industry. Deep Learning Summit is an event of its kind where we are helping the delegates build their own AI application using Deep Learning.
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Deep Learning Summit - Build Real Applications
... Deep Learning Summit - Build Real ...
Raleigh, United States
1-10 Employees
2014
We are 100% focused on Machine Vision, Deep Learning, and related disciplines. We are diligent in taking the time to understand your unique requirements regarding performance, reliability, and adaptability. From there, we develop a vision script, and results and performance tabulated. We provide industrial vision solutions for inspection, identification, gauging, barcode reading, OCR, guidance, 3D vision, and image-based deep learning. By taking the philosophy of: If it doesn't have a camera on it, we are not involved, this allows us to hone our craft for both depth and breadth. With a solid background in controls, software development, image processing, and optics, we can provide machine vision services in all complexity tiers. And can provide stand-alone turnkey vision systems and retrofits with Cognex Dataman, Cognex In-Sight, Cognex VisionPro, or MvTec Halcon for a wide range of industries. Industrial Machine Vision systems help to ensure the quality of your product and can be designed so that they are maintenance friendly.
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Portfolio - Machine Vision & Deep Learning Projects - Deep Learning
... Portfolio - Machine Vision & Deep Learning ...
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The Deep Learning Team - Building DataSets for AI Models
... We are a Deep Learning and AI service provider that builds industry-specific deep learning and AI models in Tensorflow, Pytorch, Apache MXNet, and Keras. We build for IOS, Android, and enterprise business applications. ...
Chesterfield, United States
1-10 Employees
2015
LIT AI is at the forefront of AI innovation, offering a groundbreaking platform that is industry-agnostic. LIT AI solutions can be deployed in healthcare to more efficiently triage patients, improve the accuracy of disease diagnoses, development of more efficacious pharmacological solutions, and improve clinical outcomes. LIT AI can help businesses optimize operations, customer service, inventory management, sales forecasting, and uncover new consumer insights. LIT AI automates 90% of the workflow required to train and deploy predictive and generative AI models. While LIT AI’s primary benefits streamline and enhance your AI processes, the under-the-hood features set it apart. With LIT AI, 90% of the typically tedious workflow associated with training and deploying AI models is automated. The primary advantages of LIT AI are evident in its seamless user experience and its robust capabilities. LIT AI is optimized to tackle even the most intricate AI challenges while maintaining a user-friendly interface.
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Deep Learning
... Deep Learning ...
Timișoara, Romania
1-10 Employees
2016
We are a group of experienced software engineers, each of us having 12+ years of SW development experience in the following areas: embedded Linux, RTOS, CUDA, C++, Python, Java, AWS, and machine learning. We provide both on-site training as well as training in our IoT lab in Timisoara. We are a group of SW engineers who, at some point in their career, have worked with at least one of the other colleagues. We are proud to collaborate with Autoliv in the Volvo DriveMe project, an innovative project which aims to bring 100 Volvo XC90 cars in real traffic conditions near Göteborg, Sweden. We are a group of experienced software engineers, each of us having 12+ years of SW development experience in the following areas: embedded Linux, RTOS, IoT, C++, Python, AWS, and deep learning. We provide both on-site training as well as training in our IoT laboratory in Timisoara. We offer R&D services for your Autonomous Driving or IoT projects. We act as a private research group, and offer training services in areas related to AD: Machine Learning, RTOS and RT programming, IoT and AWS IoT, Cybersecurity, Embedded Linux, Advanced C++, Python, MicroPython.
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We teach IoT and deep learning
... Join us and learn IoT, deep learning, embedded Linux, RTOS, C++ and Python, both on premise and in our IoT ...
Toulouse, France
1-10 Employees
2022
Tagging and data-mining are key elements of the final product. All the anotations work and data-centric model building is created efficiently and provided to the client. Applying Deep Learning to the specifics of satellite imagery is a real passion! Further research and specific training will probably be needed to achieve state-of-the-art performances. Aircraft detection is a recurrent subject for automatic detection in optical satellite imagery. The model has been trained on a combination of satellite images from various providers. Extracting pylons from satellite images is a subject in itself because these objects are mostly hollow and often can only be detected through their shadow in satellite images. This is a typical mix of deep learning techniques and precise measurement based on space technologies.
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Deep Learning for Earth
... Deep Learning Training applied to Earth ...
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Artificial Intelligence, Deep Learning & Machine Learning Solution Company!
... The Perceptron Global - UK | Artificial Intelligence, Deep Learning & Machine Learning Solution ...
Technologies which have been searched by others and may be interesting for you:
Some interesting numbers and facts about the results you have just received for Deep Learning
| Country with most fitting companies | United States |
| Amount of fitting manufacturers | 1841 |
| Amount of suitable service providers | 1329 |
| Average amount of employees | 1-10 |
| Oldest suiting company | 2014 |
| Youngest suiting company | 2022 |
Deep learning is a subset of machine learning, distinguished by its capability to process and learn from vast amounts of data through neural networks with multiple layers. These neural networks mimic the human brain's structure and functioning, enabling the algorithm to learn from data in a hierarchical manner. As data passes through each layer, the system identifies and distinguishes features with increasing complexity, refining its learning and decision-making processes. This technology has been pivotal in advancing numerous fields, notably in image and speech recognition, natural language processing, and autonomous vehicles. Its impact extends to enhancing the precision of medical diagnoses, streamlining predictive maintenance in manufacturing, and personalizing user experiences in digital platforms. Deep learning's ability to autonomously learn from data, identify patterns, and make decisions with minimal human intervention marks a significant evolution in artificial intelligence, opening new frontiers for research, innovation, and automation. Its role in processing and analyzing the exponentially growing data in today's digital age is indispensable, offering insights and solutions that were previously unattainable. Through its advanced capabilities, deep learning continues to drive progress across various sectors, transforming industries and shaping the future of technology.
1. Enhanced Data Processing
Deep learning algorithms excel in handling vast amounts of data. They can identify patterns and insights from data that are too complex for traditional algorithms, improving decision-making and predictive analytics.
2. Improved Accuracy
As more data is fed into deep learning models, their accuracy in tasks such as image and speech recognition improves significantly over time. This capability surpasses that of other machine learning methods, offering more reliable and precise outcomes.
3. Autonomous Feature Extraction
Deep learning models are capable of automatically discovering the representations needed for feature detection or classification from raw data. This eliminates the need for manual feature extraction, making the development of algorithms faster and more efficient.
4. Adaptability
These models are highly adaptable and can be applied to a wide range of fields, from autonomous vehicles to medical diagnosis, showcasing their versatility and potential to revolutionize various industries.
While evaluating the different suppliers make sure to check the following criteria:
1. Technical Expertise and Experience
Ensure the supplier has a strong background in deep learning projects, with a portfolio that showcases their capability in handling complex tasks and delivering innovative solutions.
2. Data Security and Privacy Measures
Verify the supplier's commitment to data security, ensuring they have robust measures in place to protect sensitive information and comply with relevant data protection regulations.
3. Customization and Scalability
The supplier should offer customizable solutions that can scale according to your project's requirements, allowing for flexibility and growth as your needs evolve.
4. Support and Maintenance
Look for suppliers that provide ongoing support and maintenance services, ensuring your deep learning applications remain up-to-date and perform optimally.
5. Cost-Effectiveness
While not compromising on quality, the supplier should offer competitive pricing, ensuring you get value for your investment without exceeding your budget.
6. Client Testimonials and References
Seek out feedback from previous clients to gauge the supplier’s reliability, customer service quality, and the overall satisfaction level of their delivered projects.
Deep learning technology is revolutionizing the way businesses operate across various sectors. In the manufacturing industry, it's being leveraged for predictive maintenance. By analyzing vast amounts of data from machinery, deep learning algorithms can predict when equipment might fail, allowing for proactive maintenance that minimizes downtime and reduces operational costs. In the realm of finance, deep learning plays a pivotal role in fraud detection. Financial institutions utilize these algorithms to sift through millions of transactions in real-time, identifying patterns and anomalies that may indicate fraudulent activity. This capability significantly enhances security measures and protects against financial losses. Healthcare is another sector benefiting from deep learning, particularly in diagnostic imaging. Algorithms trained with large datasets of medical images can assist radiologists in identifying diseases such as cancer at early stages with remarkable accuracy. This application not only improves patient outcomes but also streamlines the diagnostic process. Lastly, in the customer service industry, deep learning is transforming chatbots and virtual assistants. These AI-driven tools can understand and process natural language queries, offering personalized and efficient responses to customer inquiries. This improves customer satisfaction and operational efficiency, showcasing the versatile applications of deep learning in enhancing business operations.
Deep Learning, a subset of machine learning in artificial intelligence, has advanced to a high Technology Readiness Level (TRL), typically between 7 to 9, depending on the specific application and sector. This high TRL is attributed to its successful integration and operational effectiveness in various real-world applications, including natural language processing, image recognition, and autonomous vehicles. The technical underpinning for this maturity level lies in the significant improvements in algorithmic efficiency, data processing capabilities, and the exponential increase in computing power, particularly through GPUs and specialized hardware like TPUs. The availability of large datasets, essential for training deep learning models, has also played a critical role. Furthermore, the development of sophisticated neural network architectures, such as Convolutional Neural Networks (CNNs) for image tasks and Recurrent Neural Networks (RNNs) for sequential data, has enhanced the performance and applicability of deep learning solutions. These advancements have led to demonstrable reliability and effectiveness in complex environments, pushing deep learning technologies into the higher echelons of the TRL spectrum, showcasing their readiness for widespread commercial and industrial deployment.
In the short-term, deep learning is poised to see significant enhancements in efficiency and accessibility. Advances in algorithm optimization will lead to faster training times and lower computational costs, making deep learning more accessible to a broader range of users and industries. Additionally, the development of more user-friendly interfaces and tools will democratize deep learning, allowing non-experts to leverage this technology for innovative applications across various sectors including healthcare, finance, and retail. The mid-term outlook for deep learning predicts a leap in cognitive capabilities, bridging the gap between AI and human-like understanding. Innovations in unsupervised learning algorithms will enable systems to learn from unstructured data without human intervention, paving the way for more intuitive AI systems. These advancements will foster the creation of AI that can understand context, make inferences, and possess emotional intelligence, thereby enhancing its applicability in nuanced fields such as personalized education, empathetic customer service bots, and advanced predictive analytics. Looking into the long-term, deep learning is expected to revolutionize the interaction between humans and technology, leading to the emergence of autonomous systems with capabilities surpassing current predictive models. Breakthroughs in quantum computing will likely accelerate deep learning processes exponentially, enabling the analysis of complex datasets in real-time and facilitating real-world applications that today seem like science fiction, such as fully autonomous cities, advanced human augmentation, and highly personalized medicine. These developments will not only transform industries but also redefine the human experience, blurring the lines between digital and physical realities.
