Mlearning.ai

APRIL 8, 2023

The earlier models that were SOTA for NLP mainly fell under the traditional machine learning algorithms. These included the Support vector machine (SVM) based models. 2003) “ Support-vector networks ” by Cortes and Vapnik (1995) Significant people : David Blei Corinna Cortes Vladimir Vapnik 4.

Natural Language Processing 98

Natural Language Processing Algorithm Machine Learning Machine Learning 98

Becoming Human

MARCH 16, 2023

Overhyped or not, investments in AI drug discovery jumped from $450 million in 2014 to a whopping $58 billion in 2021. Since the advent of deep learning in the 2000s, AI applications in healthcare have expanded. AI drug discovery is exploding. A few AI technologies are empowering drug design.

AI 139

AI AI Artificial Intelligence Artificial Intelligence 139

PyImageSearch

NOVEMBER 13, 2023

Home Table of Contents Faster R-CNNs Object Detection and Deep Learning Measuring Object Detector Performance From Where Do the Ground-Truth Examples Come? One of the most popular deep learning-based object detection algorithms is the family of R-CNN algorithms, originally introduced by Girshick et al.

Deep Learning 118

Deep Learning Deep Learning Algorithm Support Vector Machines 118

Mlearning.ai

FEBRUARY 15, 2023

Uysal and Gunal, 2014). Deep learning models with multilayer processing architecture are now outperforming shallow or standard classification models in terms of performance [5]. Prediction of Solar Irradiation Using Quantum Support Vector Machine Learning Algorithm. Ensemble deep learning: A review.

Cross Validation 52

Cross Validation Decision Trees Natural Language Processing Algorithm 52

Mlearning.ai

JUNE 8, 2023

Sentence embeddings can also be used in text classification by representing entire sentences as high-dimensional vectors and then feeding them into a classifier. How can we make the machine draw the inference between ‘crowded places’ and ‘busy cities’?

Machine Learning 52

Machine Learning Machine Learning Clustering Database 52