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Deep Learning Bootcamp
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



 
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