Top 10 Machine Learning Development Companies Seattle

by Zazz January 15, 2020 Time to Read Blog: 4 minutes

Machine Learning has been reshaping and transforming the businesses since its inception. We as an industry leader are not only aware of its benefits but also helping companies to make informed decisions. If you are looking for machine learning projects for your projects, have a look at top 10 machine learning development companies in Seattle.

  • Zazz Logozazz


    Zazz is an American digital agency that has been at the forefront of software design & development innovation. As an industry leader, Zazz team pride ourselves in adopting, iterating & investing in the latest technologies, seamless processes and creative talent.

    At Zazz leverage a bottom up approach to software development, whereby the user is the centre of our universe - It’s their journey, footprint and engagement metrics that define the over arching digital experience.

    List of Services:


    Be it a scaling startup looking to A/B test an MVP, an SME looking to optimize a set of processes, or an enterprise seeking a digital transformation, Zazz have the experience and resources to facilitate your project’s end to end needs.

    Zazz has architected and maintained digital solutions for hundreds of VC backed Startups, government agencies and fortune 500 companies. Visit our website for detailed case studies, or grab a coffee with one of our consultants (They’re always down to geek out on the latest tech).

  • AppstudioAppStudio


    Appstudio is a full service software design and development company located in the heart of Toronto. We are pioneers in disruptive technology, with a core focus on Mobile and Web Applications. With a young, creative team, Appstudio  strive to collaborate with our clients to create truly memorable digital experiences. Whether you are startup or Enterprise, Appstudio have the resources and price-point to service your mobile requirements.

    List of Services:

    • Product Strategy
    • Prototyping & Concept Development
    • Product Design
    • Android App Development
    • iOS Application Development
    • Flutter App Development
    • Healthcare App Development
    • React Native App Development
    • IoT App Development
    • Web Application Development
    • Blockchain Development
    • Machine Learning

  • STX Next

     We are Europe’s largest Python software house. We have over 200 PythonJSReact Native and full-stack developers ready to supercharge your project with extraordinary code, the Agile way.

  • Intellias

     Intellias was founded in 2002 and by 2019 has evolved into a 1,600+ people strong supplier of software development services, with a core delivery base in Ukraine, development office in Poland and local presence in Germany. We have been delivering solutions to Fortune 500 companies and helping leading technology innovators build their software products in a variety of domains.  

  • Fayrix

     Fayrix provides world-class custom & offshore software development. Relying on 14 years of experience and a talented team of 1500+ IT professionals including 700+ developers, we are ready to execute software development projects of any scale. We provide to our clients flexible terms, competitive rates & different models of partnership - time & materials, dedicated teams or project-based full outsourcing.

  • Neoteric

     We are Neoteric and we help startups and enterprises build successful software ventures providing end-to-end product development services, extending our partners with product teams and implementing AI.

  • NeuroSYS

     We combine analytical and consultancy skills with a full-cycle software development to create individually tailored solutions that meet your business needs. Being innovation-driven, we also provide services in area of Artificial Intelligence, and Deep Learning, and develop solutions for the commercial application of these technologies.

  • MobiDev

     MobiDev provides custom software development.   Main areas of expertise: ➤  Web development ➤  Mobile development (iOS/Android and cross-platform) ➤  Augmented Reality ➤  IoT & Hardware Integration ➤  Artificial Intelligence. Data Science & Machine Learning ➤  Microservices & Cloud infrastructure

  • Altoros

     Altoros is a 400+ person strong consultancy that helps Global 2000 organizations with the methodology, training, technology building blocks, and end-to-end solution development required to support digital transformation at scale. We turn cloud-native app development, customer analytics, blockchain, and artificial intelligence into products with a sustainable competitive advantage.

  • Netguru

     Netguru builds digital products that let people do things differently. As a company, we deliver digital products for top startups, Fortune500 companies, and well-known brands to help them solve real problems through software and product design. Our clients have changed the way people do banking, listen to music, learn languages and rent bikes. Their products have been featured in TechCrunch, Business Insider and Product Hunt.

Machine learning – the branch of artificial intelligence – is changing not only the way we interact with machines but also how we interact with the environment around us. In the last decade, machine learning has given us cars that drive by themselves, voice recognition, effective web searches, personalized recommendations, and a vast understanding of the human genome. The term “machine learning” dates back to 1959 when Arthur Samuel, an IBM researcher defined it as “the ability (for computers) to learn without being explicitly programmed,” and this field encompasses a variety of mathematical techniques where computers learn and redefine their solutions based on a simple “training” of data. But how does machine learning work?

Computers were originally designed to follow algorithms. An algorithm is simply a series of stages encoded in a computer language. Expert computer programmers would contact process experts to plan business operations in flowcharts which would then be implemented as computer programs. A flowchart explicitly positions the tasks that must be performed, in the order in which they should be performed, along with any decision that needs to be made along the way. Flowcharts are excellent for modeling repetitive and predictable processes where decisions are made on unambiguous data. These systems were created to be decisive.

But not all processes follow clear and immutable rules, and many real-world decisions do not lead to a single unambiguous answer. Machine learning systems are probabilistic: tasks are executed and decisions are made on incomplete information and the results are assigned probabilities of being correct. Machine learning is suitable for problems that involve classification (dividing objects between two or more classes) regression (discovering relationships between variables) and grouping (grouping objects with similar characteristics). Which brings us to certain uses such as:

Recognize patterns:

  • Objects in real scenarios
  • Facial Identities or Expressions
  • Spoken language
  • Extract knowledge:
  • Of free format, audio or video texts
  • Email spam detection

Discover abnormalities:

  • Unusual sequences of financial transactions
  • Unusual patterns of sensor readings
  • Make predictions:
  • Future value of the shares or exchange rates
  • What movies will a person like?

Many mathematical techniques support machine learning, the most important are these:

Linear and polynomial regression

Regression deals with modeling the relationship between numerical variables that is iteratively refined using an error measure in the predictions made by the model. The basic assumption is that the output variable (a numerical value) can be expressed as a combination (weighted sum) of a set of numerical output variables.

Decision trees

These tree-shaped flowcharts use ramifications to illustrate any possible outcome of a decision. Many of these tree diagrams use binary branching (two options) based on current values ​​or data attributes. For large volumes of data, many of these multiple decision trees can be created, which together form a consensus decision on the results. Decision trees can be used for classification and regression problems.

Neural networks

This concept is inspired by the way the nervous system works, as well as the brain to process information. A large number of highly interconnected processing elements work in unison to solve specific problems, usually of classification or pattern matching. Each neuron “votes” on the outcome of the decision, which could urge other neurons to vote, so the votes are counted creating a classification of the results depending on the support each has received.

Bayesian network

These graphic structures, also known as a belief network, are used to represent knowledge about an uncertain domain. The graph is a probabilistic map of causes and effects where each node represents a random variable, while the edges between the nodes represent probabilistic dependencies. For example “red sky at night” could lead to a 75% chance of “good weather.” These conditional dependencies are frequently estimated using statistical and computational methods.

Markov chains

They are mathematical systems that go from one “state” (situation or group of values) to another: it is assumed that future states depend only on the present state and not on the sequence of events that precede it. For example, if you make a model of the Markov chain about the behavior of a baby, you could include “play”, “eat”, “cry” and “sleep” as states, which together with other behaviors could form a “space of states ”which would be a list of all possible states. Additionally, a Markov chain tells you what is the probability of jumping or “transcending” from one state to another, for example, the probability that a baby that is playing falls asleep in the next five minutes without crying before.

The plethora of algorithms available for machine learning has restricted this technology to those companies with the experience required to select the right tool for the project at hand. For machine learning to be more widely adopted, these technologies need to be simplified and delivered as a service. This is the goal of the IBM Watson machine learning service.

Created on Apache Spark, Watson machine learning intelligently and automatically builds models using open machine learning libraries and the most understandable algorithm groups in the industry. Its patented cognitive assistance for data science technology marks each machine learning algorithm against the data provided to recommend the best solution for the need.

Also Read:

A Layman’s Guide to Deep Learning and its benefits

How Machine Learning is Modernising the Banking Sector

Top 10 Machine Learning Development Companies Seattle
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Top 10 Machine Learning Development Companies Seattle
Machine Learning has been reshaping and transforming businesses since its inception. We as an industry leader are not only aware of its benefits but also helping companies to make informed decisions. If you are looking for machine learning projects for your projects, have a look at the top 10 machine learning development companies in Seattle.
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Zazz has since been committed to facilitating services that go beyond excellence. We create apps to meet the needs of an evolving digital landscape. We are a leading mobile app development company . We design & develop web & mobile apps that drive today's businesses. Backed by research and development, Zazz uses technology, software, mobile, and customer service to create new revenue-generating opportunities. So contact Zazz to see your dream idea as the next big thing. We Offer Top Services iOS App Development , Android Application Development Services, React development , Flutter development , IoT Development , AR / VR development , Digital Marketing Services - SEO , SMO , PPC , Ecommerce App Development, cloud app development, front end development, education app development services, Mean Stack Web Development, Content Marketing, etc.

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