Maîtrisez l'Intelligence Artificielle
Maîtrisez les concepts fondamentaux du machine learning et du Deep learning et créez vos propres intelligences artificielles. Des ateliers pratiques sur les principales applications d'IA: Computer Vision, Multimedia Object Analysis and Classification, Sentiment Analysis, Natural language processing ,Data Analysis, ...
Premier jour 18 Décembre 2023
Supervised Machine Learning (Classification)
Artificial Intelligence: Overview
How to design a Machine Learning based System? Steps & Deliverables
Similarity based algorithm: Euclidean Vs Cosine distances
Probability based algorithm: Naive Bayes
Boundary Decision based algorithms: Support Vector Machines & Neural Network
How to evaluate a classification? Confusion Matrix, Recall, Precision, F1-score, g-mean, Accuracy
Practical sessions 1 and 2: Experimental Studies on Classification of Flowers data and authentication data
Deuxième jour 19 Décembre 2023
Deep Learning using CNN for Classification
Deep Learning:Overview
Detailed Explanation of Convolutional Neural Network for Image classification
Hyper parameters tuning of CNN architectures
Transfer learning of pre-trained Models on ImageNet
Practical sessions 3 and 4: CNN from scratch for COVID-19 Detection from X-Ray images (Binary Classification) and Car Model Detection from RGB images (MultiClass Classification)
Practical sessions 5 and 6: CNN Transfer learning for COVID-19 Detection from X-Ray images (Binary Classification) and Car Model Detection from RGB images (MultiClass Classification)
Troisième jour 20 Décembre 2023
Supervised Machine learning and Deep Learning for Regression
Regression and Problem Formulation
Statistical Algorithm for Regression: Linear Regression
Machine Learning for Regression: Long Short Term Memory (LSTM)
Design of an LSTM Architecture for Regression, Hyper-parameters Tuning of LSTM
How to evaluate a regression model: MSE, MAE, MAPE
Practical session 7: Statistical Algorithm for Regression: Linear Regression on airline passenger data
Practical session 8: LSTM for Regression on airline passenger data
Quatrième jour 21 Décembre 2023
Unsupervised Machine learning (Clustering & Dimensionality Reduction)
Clustering and Problem Formulation
K-means for Clustering
How to evaluate performance of a clustering?
Practical session 9: Clustering using K-means on Authentication Data
Reduction of Dimensionality using Principal Component Analysis and Correlation Matrix
Practical session 10: How to evaluate the relevance of features using Pearson Moments
Unsupervised Learning using Deep Learning Auto-encoder (AE) for Features Transformation
Practical session 11: AE using K-means on Authentication Data
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Le tarif est de 1500 dinars TTC (475 euros) qui couvre les frais de la formation (4 jours), les pauses-café, bloc-notes, supports pédagogiques ainsi que l’hébergement pour 3 nuitées en all-inclusive à l'hôtel Rosa Beach Monastir. Le tarif sans hébergement est de 1050 dinars TTC ( 330 euros).
École d'hiver de la technologie
(21-24 Décembre 2022)
L' école d'hiver de l'embarqué et de l'Intelligence artificielle dans sa quatrième édition a permis au participants de découvrir les différentes plateformes émergentes de nos jours: Raspberry pi 4 et ESP32. Des ateliers diversifiés sur la commande à distance, domotique, robotique, computer vision, IoT, deep learning, machine learning, Natural Language Processing, Datamining, ...
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