Our Expertise in Java Frameworks
To deliver fast, streamlined and competitive services, we have armed our Java developers with the best Java frameworks, tools and technological aids. It not only makes the development work easy for our developers, but helps us deliver flawless projects faster. Hire Java Application Development experts from Mad for best end-results
Mad utilizes the best Java Development frameworks in order to build premium-quality solutions. Our Java specialists make use of famous Java frameworks like Spring, Struts, Grail, Blade, JSF, PrimeFaces, JHipster, GWT, Dropwizard and more. We always pick the most optimal framework for your project.
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4 to 6 Years of Exp. Java Developer
In short, we do everything which an enterprise might need to get done. Knowing ins and outs of Java and using the best tools & technologies to utilize its power is what makes us the best Java Development Company for everyone looking for quality services.
Madhurebba offers comprehensive Java Development services to its client, while our focus remains at delivering robust and quality-driven solutions every single time. With a right blend of language’s knowledge, required tools, insights of the framework and efficient human resources in our Java Development company, there is nothing we cannot deliver.
Our developers are experienced, equipped with the best technological aids, energetic and dedicated to helping businesses get what they want. We can work for businesses as well as IT companies, looking for outsourcing their overflowing projects with equal efficiency. Hire Java developers for short-term or long-term association from Bacancy Technology.
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Apart from prediction and classification, in what other projects I can use AI and ML?
- Image Processing (Correct image quality, Image Analysis, Image Synthesizing, Image Captioning)
- Text Generation (For Q&A, Chatbot Response, Text Summarization)
- Video Processing (Identifying actions and humans present in the video, Video summarization)
How much data is required to build an AI and ML-based solution?
What specific type of data is required to implement AI and ML?
- Tabular data
What are the limitations of AI and ML?
- Unavailability of a large number of training samples.
- Labeling of Data – As deep learning and conventional machine learning algorithms are supervised, i.e., they need data and their label to capture the semantics of work to be done. It is a manual process and eats up more time than actually building models. It also adds biases in data as humans are prone to error when it comes to accurately annotating data, e.g. Annotating car parts for detecting damage. Model build with such data generally doesn’t converse with reasonable accuracy.
- Adopting Generality – Ml/DL algorithms are not able to produce the same results when deployed to different scenarios than the scenario used while training. So, to make it work in a different situation, a retraining model is required.
- Unable to explain what is going on inside the model and hence challenging to debug. However, various analytical tools can help with this.