Madhurebba is an award-winning web and mobile app development company. In the age of mobile apps evolution, we are considered as grandpa in the app years.
After working more than a decade in the same industry, I found MadhuRebba Technology. I wanted to bring digital crafters on the same platform to channelize those resources and ignite their spark to achieve limitless potential for the betterment of stakeholders.
Madhurebba is not an average IT company and we’re not an average mobile app developers. Hiring our team is like experiencing a top-notch development team, working with premium design studio, a strategic business consultant, a product manager, a marketing guru, a numbers cruncher and a tech geeks – all in one.
– Chandresh Patel
Free Mobile App Consultation
Madhurebba provides a free in detail consultation to clearly understand your business objectives, goal, vision and mission. We also provide you free access of our skillful minds, so you can measure their skillful expertise and have clear idea as well as a detailed idea about the scope of work.
We Provide To Our Prospective Clients:
Free In-Depth App Consultation
Our consultants willingly provide as many free consultation sessions as it takes to precisely understand your technical requirements. We are here to help you to take your app idea to the next level.
Continuous Delivery Approach
We apply a continuous delivery approach for the listed below reasons: a chance to build a quality product, accelerated time to market increased reliability and process automation. We provide years of experience and expertise to help you make the right decisions.
Is 15 days risk-free trial period completely free?
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.