Building AI Solutions Using Advanced Algorithms and Open Source Frameworks
Issued by
IBM
This badge earner demonstrates knowledge and understanding in technical and scientific concepts related to building AI solutions with open-source frameworks (such as TensorFlow and Keras) to make model predictions using regression, classification, and clustering algorithms such as Naive Bayes, Logistic regression, K-nearest neighbors, Polynomial Linear Regression, SVM (Kernel), Decision tree, and Ensemble learning, K means and DBSCAN for anomaly detection and computer vision.
- Type Learning
- Level Intermediate
- Time Days
- Cost Free
Skills
- AI
- AI Pipelines
- Anomaly Detection
- Backpropagation
- Caffe2
- Classification Algorithms
- Clustering Algorithms
- Computer Vision & CNN Architectures
- Convolutional Neural Networks (CNNs)
- DBSCAN moons
- Decision Tree Algorithm
- Ensemble Learning
- High Dimensional Vector Spaces
- Keras (Neural Network Library)
- K Means
- K-Nearest Neighbors Algorithm
- Logistic Regression And Multivariate Statistical Models
- Model Predictions
- Naive Bayes Classifier
- Neural Networks And Deep Learning
- Open Source Frameworks
- Perceptrons & Neural Network Algorithms
- Polynomial Linear Regression
- PWID-B0625900
- PyTorch (Machine Learning Library)
- Recurrent Neural Networks (RNNs)
- Regression Algorithms
- Restricted Boltzmann Machines
- Support-vector Machines
- TensorFlow
- Tensors
- Theano (Software)
- Torch (Machine Learning)
Earning Criteria
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Must have completed the self-paced online course activities, and knowledge checks validating understanding of the covered topics.