Artificial Intelligence without coding, create great solutions, forecast and more
Free tutorial
2,919 students
34min of on-demand video
Created by Kenneth Alvarenga
English
What you’ll learn
- Machine learning
- Data visualization
- Create a workflow of machine learning algorithm
- Linear regression
Requirements
- No experience required, the course start from cero
Description
In last couple of years, machine learning has become a fundamental tool for decision-making in the corporate world, as well as widely used in different areas, ranging from business to the purest science, allowing the computer to perform the most difficult tasks finding patterns and correlations between variables that allow through inferential statistics to make predictions based on data, which allows creating competitive advantages in various fields, taking advantage of the inputs of historical information of the company or business to find patterns and correlations that allow us to identify possible future outcomes. Under the supervised learning paradigm we will apply the concept of linear regression to project, through the equation of the line, the possible result values in relation to predictor variables and dependent variables, in which Machine Learning is able to identify the weights of importance for each one of the participating variables, its relationship with the variable of interest to be predicted and even determine if any system variable can be discarded, in order to create a model with a high level of statistical reliability that contributes to the decision-making process management, finally one of the objectives of the course is to also understand the importance of data visualization to achieve a greater understanding of the results of the model and thus identify how far or close to the actual results selected to evaluate the model we are
Who this course is for:
- decision makers, data analist, students, and people interested in learn to use machine learning
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Course content
13 sections • 15 lectures • 34m total lengthCollapse all sections
Thank you for your support1 lecture • 1min
- Let me know if you want more Machine Learning examples00:38
Introduction3 lectures • 6min
- Speed showcase of the Knime tool02:27
- Download and Install KNIME01:29
- KNIME Interface02:10
Creating a workspace group and a workflow project1 lecture • 2min
- Creating a workspace group and a workflow project01:43
Load a table data1 lecture • 3min
- Load a table data in Excel file format03:28
Scatter matrix Graph1 lecture • 5min
- Scatter matrix Graph04:36
Partitioning data to train and test our model1 lecture • 3min
- Partitioning data to train and test our model02:46
Machine learning for linear regression1 lecture • 3min
- Linear regressión learner02:37
Machine Learner Predictor1 lecture • 2min
- Make a prediction over the remaining Test Data01:34
Mesure the effectiveness of the model with Numeric Scorer1 lecture • 2min
- Mesure the effectiveness of the model with Numeric Scorer02:08
Visualization of the result1 lecture • 2min
- Visualization of the result for better understanding01:59
Predict over new data (Working model)1 lecture • 4min
- Predict over new dataset – Week 7 Budget04:29
Export results to an excel file1 lecture • 2min
- Export results to an excel file02:15
Extra class1 lecture • 1min
- Extra class00:05
