|
Machine learning/AI Training Overview
Targeted to professionals starting out with deep learning, this program will leave you familiar with the basics of deep learning. You will learn about and get to implement and practice applying neural networks, including convolutional networks and sequence (RNN, LSTM) models, and learn best practices for developing deep learning systems.
Machine learning/AI Training Course duration
10 Days
Machine learning/AI Training Course Objectives
After this course a student should be able to
- Understand deep learning basic concepts and terminology
- Learn how to leverage deep neural networks to solve real-world image classification problems, how to detect objected using trained neural networks, and how to train and evaluate an image segmentation network
Machine learning/AI Training Course outline
Part 1 - Data Preprocessing
Part 2 - Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, SVR, Decision Tree Regression, Random Forest Regression
Part 3 - Classification: Logistic Regression, K-NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest Classification
Part 4 - Clustering: K-Means, Hierarchical Clustering
Part 5 - Association Rule Learning: Apriori, Eclat
Part 6 - Reinforcement Learning: Upper Confidence Bound, Thompson Sampling
Part 7 - Natural Language Processing: Bag-of-words model and algorithms for NLP
Part 8 - Deep Learning: Artificial Neural Networks, Convolutional Neural Networks
Part 9 - Dimensionality Reduction: PCA, LDA, Kernel PCA
Part 10 - Model Selection & Boosting: k-fold Cross Validation, Parameter Tuning, Grid Search, XGBoost
Part 11-Practical Labs in:
Automatic Machine Translation
Object Classification and Detection
|
