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This training will get you fully up to speed with Microsoft’s new MLNET machine learning library.
You will learn all about regression, binary and multiclass classification and clustering. You’ll also master popular learning algorithms like gradient descent, the decision tree, bagging and boosting ensembles and k-means clustering.
As you progress through the training material, you’ll design, train, and evaluate many complex machine learning models on your own computer in Python with the Microsoft MLNET machine learning library.
I will provide you with all the datasets, source code and libraries you need to get started and build your own machine learning apps.
The training covers the following topics:
Supervised Machine Learning
Loading Numeric Data
Normalization
Processing Outliers
Processing Missing Values
Loading Text Data
One-Hot Encoding
Sparse Vector Encoding
Loading Geo Data
Binning
Vector Cross-Products
Single Linear Regression
RMSE, MSE and MAE
Gradient Descent
Multiple Linear Regression
Binary Classification
Accuracy, Precision and Recall
ROC, AUC and Bias
Multiclass Classification
The Confusion Matrix
Micro and Macro Average
Overfitting
Underfitting
Partitioning Datasets
Minibatch Training
K-Fold Cross Validation
Decision Trees
Classification Trees
Regression Trees
Bagging Ensemble Models
Boosting Ensemble Models
Stacking Ensemble Models
Unsupervised Machine Learning
K-Means Clustering
The Davies-Bouldin Index
Check out this training lesson preview in which I will show you how we can build a multiclass classification model by stacking several binary classification models on top of each other.
The video covers Multiclass Classification, Sigmoid and Softmax Activation.
Here are four lab assignments from the training. In each lab, you will be building a Python application that trains a machine learning model on your laptop using a well-known AI dataset.
Build a regression model to predict the price of a taxi trip in New York
Build a machine learning model that can recognize handwritten digits from the famous MNIST dataset
Build a regression model that predicts how many shared bikes are needed in Washington DC every day
Build a binary classification model to predict which passengers on the Titanic will survive the disaster
For this course you will need a computer (running Windows, MacOS, or Linux), Python, the Microsoft MLNET machine learning library and the NimbusML package.
Choose the plan that works best for you. Buy this course and dive into MLNET machine learning, or unlock unlimited access to every course on the site.
Want the best learning experience?
Members get access to the full course library, all labs and community pages, receive priority support and sneak previews of future course releases.
Prices shown exclude VAT. EU businesses can defer VAT during checkout with a valid VAT ID number.
Buy this course and get lifetime access to all lectures and knowledge quizzes
✔️ This course
✔️ Included quizzes only
✔️ Included labs only
🚫 No priority support
🚫 No community access
🚫 No future courses
€95 one time
Get access to all courses, lectures, labs, quizzes, and future releases
✔️ All courses
✔️ All quizzes
✔️ All labs
✔️ Priority support
✔️ Community pages
✔️ Access to future courses
€35 p/mo or €350 p/yr
In-company or online team training with guided labs and live support
🪙 Onsite or online
🪙 Conducted live
🪙 For teams of 5-12
🪙 3-day training
🪙 Guided labs
🪙 Can be customized
€1250 p/day
A concise, easy to follow, well explained, accurately depicted, and wonderfully presented five course meal! Mark has served up a real hot winner here.
The course is brilliant. Everything is clear, the trainer focuses attention on important things and repeats them so they can be remembered. Lots of real-world examples are included.
I hope I've given you a clear overview of the contents of this training course. But if anything is still unclear and you have some unanswered questions, then please check out this FAQ section
In an online training you can study the training lectures and work on the homework assignments in your own time and at your own pace. You can spend as many or as little hours per week as you want on the training.
You will receive prerecorded online video lectures, text lectures, multiple-choice quizzes and homework exercises.
You are supported through email, and you can also book a 30-minute video support call with me if you want. I will help you with the training lectures and homework projects and get you ready for your certification exams.
An online training is ideal for tech professionals who want to set their own learning pace and prefer to work independently with a bit of guidance and support throughout the training.
I host all my training content on Podia, a well-known e-learning platform based in the United States.
You have unlimited access to the online training content and your login account will never expire.
Yes! I often host classroom trainings where I teach tech subjects to an entire business team. Contact me and we'll get it organised.
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