Expected X provides a variety of services to help you bring predictive modeling capabilities into your organization. Whether you are just getting started or are already on your way and just need some extra help, we have a solution right for you.

Train Your Staff

Let us educate and motivate your staff in applying machine learning and deep learning in their roles.  Our machine learning and deep learning training workshops will teach the basics of this exciting field using one of the most powerful tools in the industry, Python.  Our Fortune 100 tested workshops can be conducted on-site or virtually.


Our Training Courses Include:

 
 
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Machine Learning and Deep Learning Fundamentals with Python

Are you ready to jump-start your team in predictive modeling and build their interest in applying these skills at work? Our 2-day on-site workshop provides an introduction to both machine learning and deep learning foundational knowledge. Additionally, participants gain hands-on experience building and testing models using the industry's most widely-used tool, Python. Expected X has successfully delivered training to Fortune 100 clients but works with organizations of all sizes. Here is a sample of our curriculum:

Details:

  • Tying ML/DL projects to measurable business outcomes

  • Applying industry-standard project frameworks

  • Understanding reality vs. hype of ML/DL

  • Deep Learning in artificial intelligence

  • In-class case study specific to your business/industry

  • ML/DL labs in Python via Google Colaboratory

Recommended for analysts and developers with some coding experience in Python

  • Introduction to Machine Learning (ML) and Deep Learning (DL)

  • Statistics, Probability, and Machine Learning

  • Machine Learning/Deep Learning Process

  • Data Cleansing and EDA

  • Machine Learning/Deep Learning Algorithms

  • Parameter Tuning and Model Evaluation

  • Deep Learning

  • Real-world Machine Learning and Deep Learning

  • Workshop Wrap-up

 

 
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Introduction to Machine Learning with Python

Our machine learning introductory course provides a more comprehensive overview of the topic and omits deep learning. This 2-day on-site workshop dives further into the topic of machine learning to give participants time to explore additional supervised and unsupervised algorithms. Participants gain hands-on experience building and testing models using the industry's most widely-used tool, Python. Here is a sample of our curriculum:

Details:

  • Tying ML projects to measurable business outcomes

  • Applying industry-standard project frameworks

  • Understanding reality vs. hype of ML

  • Non-linear regression, discriminant/factor analysis, Support Vector Machines, data reduction techniques, clustering with DBSCAN and Gaussian Mixture Models

  • In-class case study specific to your business/industry

  • ML labs in Python via Google Colaboratory

Recommended for analysts and developers with some coding experience in Python

  • Introduction to Machine Learning (ML)

  • Statistics, Probability, and Machine Learning

  • Machine Learning Process

  • Data Cleansing and EDA

  • Machine Learning Algorithms

  • Parameter Tuning and Model Evaluation

  • Real-world Machine Learning

  • Workshop Wrap-up

 

 
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Introduction to Deep Learning with Python

Our deep learning introductory course explores the foundational, theoretical, and philosophical aspects of the field. This 2-day on-site workshop gives participants additional time to work with Artificial Neural Networks, the basis for most applications in deep learning and artificial intelligence. Participants gain hands-on experience building and testing models using the industry's most widely-used tool, Python. Here is a sample of our curriculum: 

  • Introduction to Deep Learning (DL)

  • Review of statistics/probability, EDA, building business cases, and big data

  • Deep Learning Algorithms

  • Parameter Tuning and Model Evaluation

  • Real-world Deep Learning

  • Workshop Wrap-up

Details:

  • Understanding reality vs. hype of DL

  • Artificial Neural Networks (ANNs): Perceptrons, Recursive Neural Networks (RNNs), Convolutional Neural Networks (CNNs)

  • Backpropagation and hyperparameters

  • Visualizing ANNs with TensorPlayground and 2D CNN MNIST demonstration

  • DL labs in Python via Google Colaboratory with applications in Keras/TensorFlow

Recommended for analysts and developers with some coding experience in Python and previously taken "Introduction to Machine Learning with Python"

 

 


Augment Your Team

Have a project requiring predictive modeling but don't have the internal capabilities to staff it? Expected X provides the expertise to ramp up new predictive modeling projects or back-fill resources for your temporary needs. We've supported large and small businesses, from start-ups to the U.S. Department of Energy. See what we can do for you.

 
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Already well-versed in predictive modeling? Have a project that your current workforce might not be able to adequately address without additional assistance? Expected X is passionate about the value machine learning and deep learning can bring to businesses. We'll partner with your existing team to fill the gaps in your skill set including:

  • Model development, evaluation, and deployment
  • Code review and feedback
  • Reporting and visualization design and delivery
  • ML/DL Project Management
  • Problem identification and ROI measurement
  • Stakeholder/ML team communications intermediary