Machine Learning Development:
We help organizations drive business outcomes, create breakthrough results, and improve operational efficiency with advanced Machine Learning Development.
Contact Us: https://www.charterglobal.com/contact-us/
Transform Your Business with ML-enabled Solutions:
Machine learning is the future of data analysis and data modeling, the next-gen of automation. As an experienced Machine Learning development company, we help our clients create future-ready ML-powered solutions running on Machine Learning algorithms, computational intelligence, mathematical optimization, pattern recognition, and other emerging technologies.
Our ML development portfolio helps you achieve excellence in:
• Sales forecasting
• Predictive modeling
• Customer Segmentation & Value Prediction
• Faster decision making
• Big Data Analytics
Our Machine Learning Offerings
Looking for custom Machine Learning algorithms? Check out Charter Global range of Machine learning offerings and how it enables faster decision making, business process automation, and increased productivity.
Deep Learning:
Powered by an experienced team of machine learning experts, Charter Global makes it easy for your organization to drive greater profitability from your data to get real-time insights using Deep Learning services. We simplify the entire deep learning workflow starting from data management, data gathering, training, and parsing to labeling and deployment.
Predictive Analytics:
Our predictive analytics solutions empower you to take preemptive actions to minimize risk by anticipating emerging trends and patterns. Our scalable solutions give actionable insights into your existing data, customer behavior, and market and processes that drive strategic decision-making and boost business performance.
Image Analytics:
Using deep learning solutions, Charter Global has been enabling organizations to mining image data sets. Our machine learning and image analytics expertise help you build systems that mine massive image data sets and structure them to be used for strategic decision making. Our machine learning experts run algorithms on the cloud with GPU machines for training deep learning models.
Artificial Intelligence:
Being an early mover in artificial intelligence services, we have been helping enterprises accelerate their journey to AI by developing future-ready AI applications and services. We offer seamless integration of our AI solutions into your workflows to shape future outcomes, automate processes, optimize time, and boost ROI.
Natural Language Processing:
Our natural language processing services blend artificial intelligence, machine learning, text analysis, speech recognition, and sentiment analysis—and integrate it into your applications, bots, and devices—to build a next-generation digital product that understands multiple languages and terminologies to enable better decision making.
Data Mining:
We have leveraged ML algorithms for large volume data mining and web scraping to reveal insights such as correlations, patterns, trends, demand forecasting, and more. Our customized solutions harness the power of data for efficient prediction models and better decision making.
Why Choose Charter Global for Machine Learning Development Services?
• 24X7 Support
• Certified Resources
• Predict Trends
• Customer Service
• Actionable Insights
• Diverse Industry
Looking for a Machine Learning Developer? Contact us
Showing posts with label Machine Learning Development Services. Show all posts
Showing posts with label Machine Learning Development Services. Show all posts
Friday, January 22, 2021
Machine Learning Development Services
Friday, August 28, 2020
Why Machine Learning Should Matter to You?
In recent years, machine learning has taken the world by storm as more people attempt to automate processes and build their data faster. As a method of analyzing data, machine learning development allows companies to learn from the information they are able to gather without using much human interference. With the artificial intelligence being exposed to more and more data, they can adapt, learn, and produce decisions based off of that data.
As the world grows and changes, being able to analyze the trends in the market and wants of its users is absolutely crucial for a company to be on top of their industry. Machine learning services, therefore, is incredibly important. In fact, almost every single industry is using machine learning in some capacity.
Machine Learning Frees Your Employees
Machine learning lets your employees learn new skills that they would not have had time for otherwise. Rather than analyzing extensive sets of data for hours at a time, employees can focus more on things that artificial intelligence is unable to do for the business (things that fluctuate or that need human interaction in to work). Using machine learning, you can also take out the human error that can occur as well.
Using Machine Learning Allows You to Stand Up Against Competitors
Automating your processes and analyzing data with machine learning can help you do things quicker and more efficiently than your competitors. Some companies even analyze public information about competing firms with their AI, as it can clue them in on what steps that company might be taking in the future. Complex problems are suddenly turned into simple ones as data trends that were previously undetectable, are easy to find with machine learning.
Scale with Machine Learning
With the added time your employees have and the extra money your company will save by using machine learning, scalability is much more attainable. Problems that could not be solved before, are now made easy with AI and allow you to focus on combined solutions to streamline business – and in the end, scale your business.
When a company can improve their productivity, efficiency, and the processes by which they make decisions, they are exponentially better prepared to handle more work. As the company scales, their machine learning continues to adapt alongside the business and provide more solutions. Charter Global can help you implement a Machine Learning development strategy specific for your application and business. Call today to set up a free consultation.
Tuesday, March 17, 2020
3 Ways Artificial Intelligence (AI) Services will Impact the Economy in 2020 and Beyond
1) Increasing efficiency and accuracy
in our everyday work.
It’s tempting to believe that
artificial
intelligence services
can do just about anything. If tech experts are to be believed,
artificial intelligence (AI) has the potential to transform the
world. Tech entrepreneur, Elon Musk, says this would be a threat to
humanity and life as we know it.
Even though thinking among AI researchers
has evolved over the years, the future impact of AI is strongly
debated among experts.
Currently, AI
and machine learning solutions
power self-driving cars, complex ad-tech audience optimization, and a
host of intelligent agents such as Alexa, Cortana and Siri. At the
same time, leading AI experts, business owners, and analysts caution
against an overly rosy view of its current capabilities.
The hype surrounding AI’s potential has
misled many into overlooking its current utility. Eventually, AI will
redefine industries and build technologies we never thought possible.
However, business leaders and AI experts say the real value in
today’s AI lies in increasing efficiency and accuracy in our
everyday work.
2)
Preparing for The Future – The Government’s Role
Artificial
Intelligence (AI)
Solutions
holds the potential to be a major driver of economic growth and
social progress. If industries, society, government, and the public
work together to support development of this technology with
thoughtful attention to its potential and managing its risks, then
everyone will benefit.
The U.S. government has several roles to
play. Participation in conversations about important issues is key;
this is to help set the agenda for public debate. In fact, this
initiate can monitor the safety and fairness of applications as they
develop, and adapt regulatory frameworks to encourage innovation
while protecting the public.
Another utility the government can
provide is public policy tools to ensure that disruption in the
methods of work enabled by AI increases productivity while avoiding
negative economic consequences for certain sectors of the workforce.
Not only this, but the government can support basic research and the
application of AI to public good. One of those features is to support
development of a skilled, diverse workforce.
Government can apply AI to serve the
public faster, more effectively, and at a lower cost. Many areas of
public policy, from education, to defense, to environmental
preservation, and criminal justice, will see new opportunities and
new challenges driven by the continued progress of AI.
To enable these policies, it’s crucial
for the U.S. government to understand and adapt to these changes.
3)
Economic and Social Morality
As the technology of AI continues to
develop, practitioners must ensure that AI-enabled
systems are governable. This is to ensure they are open,
transparent, and understandable. In essence, AI must work effectively
with people, so that their operation will remain consistent with
human values and aspirations.
Researchers and practitioners have
increased their attention to these challenges, and should continue to
focus on them.
Developing and studying machine
learning
development services can help us better understand and
appreciate our human intelligence. Used thoughtfully, AI can augment
our intelligence and help us to chart a better and wiser path.
Charter
Global offers AI resources to a variety of different types of
projects. Consult us for expert help, and learn more about what we
can do to achieve your AI goals.
Read More:
Friday, February 28, 2020
Understanding the Difference Between Machine Learning vs. Artificial Intelligence | Charter Global
ML is technically a subset of AI.
Essentially, ML provides systems the ability to automatically learn
and improve from experience without being explicitly programmed;
focusing on the development of computer programs that can access data
and use it learn for themselves.
In other words, Machine
Learning Development
Service relies on processing big datasets, while
detecting trends and patterns within that data and essentially
“learning” about these trends along the way.
Like people, machines have the ability to
“learn,” acquiring knowledge and/or skills through their unique
experiences. For example, say you have an ML program with lots of
images of skin conditions, along with what those conditions mean.
The machine
learning algorithm
examines the images and identifies patterns, allowing it to analyze
and predict skin conditions in the future.
When the machine
learning algorithm
is given a new, unknown skin image, it will compare the pattern in
the current image to the pattern it learned from analyzing past
images. In the instance of a new skin condition, however, or if an
existing pattern of skin conditions changes, the algorithm will not
predict those conditions correctly.
This is because one must feed in all the
new data so that the algorithm can continue to predict skin
conditions accurately.
Unlike machine
learning services,
AI learns by acquiring and then applying knowledge. The goal of AI is
to find the most optimal solution possible, by training computers a
response mechanism equal to or better than that of a human being.
In the instance of adaptation in new
scenarios, Artificial
Intelligence services
is perhaps the most ideal.
Let’s take a simple video game, for
example, where the goal is to move through a minefield using a
self-driving car. Initially, the car does not know which path to take
in order to avoid the landmines.
After enough simulated runs, large
amounts of data are generated concluding which path works and which
paths do not. When we feed this data to the machine
learning algorithm, it is able to learn from the past driving
experience and navigate the car safely.
But, what if the location of the
landmines has changed? The machine
learning
algorithm does not know these individual landmines exist,
rather, it only exclusively knows the all it knows the pattern
resulting from the initial data.
Unless we feed the algorithm the new data
so it can continue learning, it will continue to guide along that
(now incorrect) path.
Enter, AI – capable of analyzing new
data in an algorithm to determine multiple factors; answering
questions like, why did the paths change? Which direction is most
ideal, given the new circumstances, and where are the new hot-spots?
It will then codify rules of those hot-spots where the land mines
exist.
Slowly, AI will begin to avoid them
altogether by following the new trails – just like people, learning
and adapting to new boundaries and environmental challenges.
The
Future is Now with AI and ML
So, by now, you’ve learned the basic
differentiating factors between ML and AI. Machine learning uses past
experiences to look for learned patterns, while Artificial
Intelligence services
uses the experiences to acquire knowledge and skills, then applies
that knowledge to new scenarios.
It’s clear that both AI and machine
learning have valuable business
applications, empowering companies to respond quickly and
accurately to changes in customer behavior and solve critical
business problems.
As the adoption of AI and ML become more
commonplace, namely predictive analytics and data science will see a
massive uptake in virtually all industries across the marketplace.
For
More Information, Please visit our website:
Look Out for These 7 Trends in the Internet of Things (IoT) | Charter Global
The internet has become a beastly
enterprise, with the past ten years seeing more technological
advancements than perhaps any other industry. The Internet
of Things (IOT),
for example, is one such advancement gaining immense traction in the
marketplace. Here are 7 IoT trends to look out for this year.
1.
Big Data Convergence:
IoT is changing the way we live and
conduct business exponentially, generating a huge amount of data in
the process. Big
data platforms, for example, are usually made for supporting
the demands of large-scale storage and for performing investigative
work.
Interestingly, IoT and big data have a
lot in common. Smart devices, for example, are now being designed
specifically for the purpose of digesting massive amounts of system
and user generated data. The cloud has proven instrumental in meeting
analytic and storage requirements in the realm of big data. Moving
forward, the junction between IoT and big data will definitely be a
trend on the rise.
2.
Data Processing with Edge Computing:
Albeit a powerful force, weaker elements
in IoT are evident in the addition of devices behind the firewall of
the network. While Securing the devices may be easy, securing the IoT
itself proves a trickier phenomenon. Thus, security measures must
exist between the network connection and the software applications
linking to the devices.
Perhaps the most notable benefits of IoT
are it’s cost-effectiveness and efficiency, especially in data
processing. Rapid-fire data processing is prominent in most smart
devices, re: self-driving vehicles and intelligent traffic-lights
(aptly coined, “smart lights”). Edge computing has been proposed
as a potential solution, gaining immense popularity.
Edge computing usually outperforms the
cloud when it comes to speed and cost. Faster processing translates
to lower latency, which is one of the premium benefits of edge
computing. Data processing with edge computing will see an uptake in
IoT
trends in the near future, for certain.
3.
Auto-ML (Machine Learning) for Data Security:
In present days, developers are tasked
with finding newer methods in which people can share data securely by
the use of block-chain-like technologies. Many industrial companies
are learning how to trust and accept the forecast of machine
learning models (otherwise known as “predictive
analytics”), and will acclimatize their operations for preventing
the downtime by model outputs.
Machine
learning model training will likely become a highly automated
process. Industrial companies in particular will increase the large
capital assets, particularly in cloud computing, in the near future.
4.
IoT – Massive Growth Coming:
When it comes to data analytics, IoT is
perhaps the most promising technology to date. Smart devices ingest
more data and information about the devices and users, and by 2020,
it is expected that IoT devices will exceed 31 billion. Today, we see
IoT devices as the major part for reporting and tracking.
IoT is capable of the extraction,
storage, and analysis of massive data stores. When coupled with other
ground-breaking technologies, like Artificial
Intelligence (AI), for example, the essential data can be
appropriately measured, filtered and categorized. IoT trends will
most definitely see an increase in the amount of “work” smart
devices are doing. What’s more, they will serve to assist data
scientists and technicians in providing powerful, insightful
suggestions.
5.
Better Data Analytics:
Chances are, you’ve heard some of the
hype and clamor surrounding artificial intelligence in modern
business practices. The merger of IoT and AI has seen many recent
developments, as the two can be used interdependently to provide e a
centralized decision-making tool for all types and sizes of
businesses.
AI and Machine
Learning Development Services that can easily identify
trends, patterns, and unique behaviors otherwise invisible to the
naked human eye. Better data analytics and the need to safeguard this
said data are two major reasons for the rise of this trend. By
collecting insights from this data, we could even suggest it be
rendered to help us make better decisions in our personal lives. The
sheer intelligence, thoughtfulness and self-learning capabilities
make this a hugely popular trend to look out for in the near future.
6.
Smart Cities to Become Mainstream:
When it comes to data collection, many
states have adopted a more technological approach – replacing or
improving upon antiquated infrastructure; integrating sensors to reap
data that proves invaluable for the purpose of urban planning and
development. Prepare yourself for the integration of IoT into just
about every sidewalk, crosswalk, highway, and byway, as data
collection becomes less of a convenience and more of an evolutionary
imperative for American progress.
Cities both nationwide and globally will
become pioneers for the great data exchanges affording accessibility
and empowering evidence for better decision-making. Ultimately, the
digestion and dissemination of this unique, all-telling data will
provide a fundamental platform for both private and public
organizations, and the citizens under their watch.
7.
Personalization of the Retail Experience:
With IoT, the efficiency of supply chain
and information
systems management has grown by leaps and bounds with respect
to retail. Sensors and other smart beacon technologies are being used
to tailor shopping experiences with ease, speed, and accuracy like
never before.
In the not-so-distant future, IoT can be
used to monitor, gauge, track, and personalize your investment
portfolio – making unique, custom trade recommendations based on
your data insights. Or, imagine getting notified immediately when a
highly-sought after product from your favorite shop is discounted via
push notification which when expanded, offers an indoor map of your
favorite shop – leading you to the exact product you desire.
The value of this trend ensures the
better integration of personalized retail experiences which
ultimately can bring upon a new era of shopping as we know it.
For
more related information, please visit our website:
Thursday, February 20, 2020
Machine Learning Services: A Valuable Enterprise
Machine Learning is a valuable player in the realm of the Internet of Things. ML and Internet of Things (IoT) have gained tremendous popularity over the past few years, considered by many as revolutionary, game changing tech. Yet, much confusion exists in terms of understanding the purpose of Machine Learning Models, along with it’s benefits and suitability for use.
Here’s a breakdown of Machine Learning, benefits of ML in AI and IoT, when it should be used, and it’s real-world applications today.
When Is Machine Learning Valuable?
In general, machine learning is valuable when you know what you want but you don’t know the important input variables to make that decision. So you give the machine learning algorithm your stated goals, or inputs. Based on Machine learning systems, and then it “learns” from the data which factors are important in achieving that goal.
The data models that are typical of traditional data analytics are often static and of limited use in addressing unstructured, fast-changing, sequestered amounts of data. When it comes to IoT, it’s often necessary to identify correlations between dozens of sensor inputs and external factors that are rapidly producing millions of data points.
In addition, machine learning development services has the ability to accurately predicting future events. Whereas the data models built using traditional data analytics are static, machine learning algorithms constantly improve over time as more data is captured and assimilated. This means that the machine learning algorithm can make predictions, see what actually happens, compare against its predictions, then adjust to become more accurate.
The predictive analytics made possible by machine learning are hugely valuable for many IoT applications. Let’s take a look at a few concrete examples.
How are Machine Learning Applications used in IoT?
1. Cost Savings in Industrial Applications:
Predictive capabilities are extremely useful in an industrial setting. By drawing data from multiple IoT sensors in or on machines, machine learning applications can “learn” what’s typical for the machine and then detect when something abnormal begins to occur.
Predicting when a machine needs maintenance via IoT data is incredibly valuable, translating into millions of dollars in saved costs. A great example is Goldcorp, a mining company that uses immense vehicles to haul away materials.
When these hauling vehicles break down, it costs Goldcorp $2 million per day in lost productivity. Goldcorp is now using machine learning to predict with over 90% accuracy when machines will need maintenance, meaning huge cost savings.
2. Shaping Experiences to Individuals:
We’re actually all familiar with machine learning applications in our everyday lives. Both Amazon and Netflix use machine learning to learn our preferences and provide a better experience for the user. That could mean suggesting products that you might like or providing relevant recommendations for movies and TV shows.
Similarly, in IoT machine learning can be extremely valuable in shaping our environment to our personal preferences.
The billions of sensors and devices that will continue to power connected devices, smart homes, and IoT devices in the coming years will generate exponentially more data. This huge increase in data will drive great improvements in machine learning, opening countless opportunities for us to reap the benefits.
Not only we will be able to predict when machines need maintenance, we’ll be able to predict when we need maintenance too. Machine learning will be applied to the data from our wearable to learn our baseline and determine when our vitals have become abnormal, calling a doctor or ambulance automatically if necessary.
Beyond individuals, we’ll be able to use that health data at scale to see trends across entire populations, predicting outbreaks of disease and proactively addressing health problems.
Although both machine learning and IoT can be over-hyped, the future of machine learning applications in IoT are worthy of that hype. We’re really just scratching the surface of what’s possible.
Read More:
Software development continues to develop and change each year. By researching the latest trends and keeping your process relevant, your business has a greater chance at success. If you are looking to build a scalable digital solution for your business, you should approach a software development company that works on the latest technology trends and implements the above technology stack.
Get in touch with our team to discuss IT staffing and software development solutions that can supersede your existing solutions on mobile and web applications.
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