Digital disruption and proliferation has multiplied communication and engagement in businesses. As a competitive asset, data is key to differentiating your company from the rest of the pack. Our big data consulting and engineering services can help your company improve decision-making, accelerate innovation, enhance the customer experience, and drive operational efficiency.
Based on the data, we build custom AI models that simplify decision-making. Outsourcing big data analysis to artificial intelligence, prevents human error, improve business efficiency and cut costs. Our deep technological expertise in Machine Learning and Artificial Intelligence development services can help you make precise predictions, gain deeper insights from your data, minimize operational expenses, and enhance customer experience. At TA, we are committed to providing the best-in-class Artificial Intelligence and Machine Learning development solutions to assist you at every level of your digital transformation journey.
For more than two decades, we have been at the forefront of artificial intelligence and machine learning development, with experience in AI/ML, predictive analytics and Natural Language Processing (NLP). Our innovative development team designs intelligent AI/ML solutions that can take your business to the next level providing out-of-the-box solutions to problems, automate tasks, and achieve superior outcomes. Our in-depth practical knowledge of the most recent AI/ML technologies enables us to provide a comprehensive suite of AI/ML services to provide scalable custom solutions to empower clients to tap into new market segments, to streamline your business functions and add intelligence to your enterprises workflow.
Leveraging open-source satellite data sources to analyze and
study water depletion in water bodies, coastal erosion,
changes in vegetation, and urbanization over long periods of
time we can offer new insights relating to climate change.
We can make use of the expanding Open Data Cube project to
help with reaching solutions relating to geospatial
analytics.
Motion capture has gained interest in many fields from both
game industry to sport analysis. We can utilize a deep
neural network trained to extract 3D joint estimations from
a 2D video to solve the business's need for reflecting
markers and pricey multi-camera systems. Our implementation
of motion capture includes taking a monocular video of a
person and translating that person's movement onto an avatar
in the UNITY game engine.
Image analytics capabilities help derive insights with
accurate recognition of objects in images and videos. We
help classify and process images for detailed analysis with
the appropriate placement of image objects into segments.
A conversational chatbot that uses artificial intelligence
and natural language processing to understand user intent,
analyze patterns in a conversation and finally use all this
to address customer queries.
A method of identifying or verifying the identity of an
individual using their face. Attendance marking can be done
based on a single image. Entry time and exit time can be
identified by individuals
Data filtering tool using machine learning algorithms to
recommend the most relevant items to a particular user or
customer based on the principle of finding patterns in
consumer behavior data.
Contextual mining of text which identifies and extracts
subjective information in source material, and helps a
business to understand the social sentiment of their brand,
product or service while monitoring online conversations
such as tweets.
Object recognition is a subfield of computer vision,
artificial intelligence, and machine learning that seeks to
recognize and identify the most prominent objects (i.e.,
people or things) in a digital image or video with AI
models. Image recognition is also a subfield of AI and
computer vision that seeks to recognize the high level
contents of an image.
IoT devices and sensors can capture gigabytes of data within
a few hours, analyzing and making sense of this large and
quick influx of data becomes ever more important for
organizations from every sector. We can offer our expertise
in handling such data not limited to but including satellite
data.
Healthcare
Sports
Pharma
Financial
Retail and E-Commerce
Entertainment and Gaming
Logistics and Transportation
Manufacturing
The client wanted to eliminate the background of the car video. Using convolutional network model, we replaced the car's background with white. We trained the model with U-net architecture, alpha matting and edge trimming to get rid of blurry backgrounds, bad lighting and dark vehicles.
The goal was to capture a dancer's monocular motion. Our motion capture approach uses a monocular video of a person to create an avatar in UNITY. The motion capture transformed a person's movements into a UNITY avatar tracking and analyzing object or person movement.
AI is basically a way to give machines human-like
intelligence. As the words "artificial" and "intelligence"
show, "artificial" means "made by humans" and
"intelligence" means "to think or understand." So, AI
basically means teaching machines how the human brain
works and what it can do. AI can be found in things like
Google's predictions, Uber's autopilot messages, and so
on.
Machine Learning is the subset of Artificial Intelligence
that lets machines learn and get better on their own,
without any help from humans. The recommendations you get
on music and videos on streaming apps are a very good
example of ML, virtual personal assistants like Alexa,
Siri are also good examples of ML.
Deep learning is a type of Machine Learning, which is
based on the way the human brain filters through
information. DL helps a computer sort through and filter
information so that it can predict and classify it. The
caption generators, image analysis tools that you often
use are examples of DL.
Python is the best and most used programming language for AI and ML due to its ease of use and the fact that it has well-written libraries such as Tensorflow and pytorch.
"Artificial intelligence" is one of the most popular
buzzwords you may have heard. AI is the process by which
machines learn to think like people. AI is based on the
idea that machines can mimic human intelligence and do
tasks in the same way that humans do. This lets machines
learn from experience, adapt to new information and do
tasks just like humans.
Artificial Intelligence is an umbrella discipline that
encompasses everything that makes machines smarter, so
it's not surprising that people frequently use the terms
interchangeably. AI is the branch of computer science that
enables machines to mimic human intelligence autonomously.
Machine Learning, on the other hand, refers to an AI
system that can automatically self-learn from the past by
intaking data and learning things that would be difficult
for humans to learn without explicit programming. The
purpose of machine learning is to enable machines to learn
from data and provide accurate results. Facebook's
auto-tagging suggestions and Google's search algorithms
are some applications of ML.
With the rise of Industry 4.0, these
terms are becoming very common. Artificial intelligence,
machine learning, and data learning are all related terms
that belong to the same field. Let's look at them one by
one.
Artificial intelligence is a broad field of computer
science that gives machines intelligence that is similar
to that of humans. The main goal of AI is to make systems
that can work on their own, like the human brain.
Machine learning is based on the idea that you can give
machines data and let them learn on their own without any
help from a person. Machine learning is all about
computers finding patterns in the data they are given,
just like people can find patterns in data sets.
Data science is an umbrella term for the study of data
systems and processes, with the goal of keeping track of
data and figuring out what it all means.