Improve Your ML Models Training
Author(s): Fabiana Clemente Deep Learning Cycling learning rates in Tensorflow 2.0 Deep learning has found its way into all kinds of research areas in the present times and has also become an integral part of our lives. The words of Andrew Ng …
Building a Custom Image Dataset for Deep Learning projects
Author(s): Dhilip Subramanian Showcasing an easy way to build a custom image dataset using google images and Microsoft bing Continue reading on Towards AI — Multidisciplinary Science Journal » Published via Towards AI …
Supermasks : A Simple Introduction and Implementation in PyTorch
Author(s): Kourosh T. Baghaei The general understanding of neural networks is that computations are required in order to adjust the weights of a neural network so that… Continue reading on Towards AI — Multidisciplinary Science Journal » Published via Towards AI …
Building a Quantize Aware Trained Deep Learning Model
Author(s): Renu Khandelwal Learn what is Quantization, different types of Quantization, and how to build a TFLite model using Quantize Aware Training. Continue reading on Towards AI — Multidisciplinary Science Journal » Published via Towards AI …
Neural Networks from Scratch (A brief Introduction for Beginners)
Author(s): Pratik Kumar Understanding the concepts along with the implementation of neural networks using Python and its powerful library — Numpy. Continue reading on Towards AI — Multidisciplinary Science Journal » Published via Towards AI …
Plant Disease Detection using Faster R-CNN
Author(s): Amrith Coumaran Deep Learning Faster R-CNN was first introduced in 2015 and is also a part of the R-CNN family. Compared to its predecessor, Faster R-CNN proposes a novel Region Proposals Network (RPN) and provides better performance and computational efficiency. The …
Flask Web Application with Python
Author(s): Sharon Lim Develop a Convolutional Neural Network model and deploy it as a web application using Flask Continue reading on Towards AI — Multidisciplinary Science Journal » Published via Towards AI …
Backpropagation Math Simplified
Author(s): Aseem Kashyap A gentle yet comprehensive guide to neural network calculus Continue reading on Towards AI — Multidisciplinary Science Journal » Published via Towards AI …
Elon Musk Neuralink: connecting your brain to AI
Author(s): Michelangiolo Mazzeschi The outline on the presentation held on the 29–08–2020 Continue reading on Towards AI — Multidisciplinary Science Journal » Published via Towards AI …
Kaggling: A Journey of Past Competitions — Part1
Author(s): Rashmi Margani Source: UnsplashHi Rashmi Deep Learning Kaggling: A Journey of Past Competitions — Part1 Techniques learned and Stay tuned with me for more. 1. Jigsaw Multilingual Toxic Comment Classification Competition In Jigsaw competition, Cross-validation, postprocessing, and preprocessing played a lot of importance. Pseudo …
Step By Step Guide In Creating Your Own Emotion Recognition System
Author(s): Nabeel Ahmed Introduction Continue reading on Towards AI — Multidisciplinary Science Journal » Published via Towards AI …
Introduction to Deep Learning with TensorFlow
Last Updated on August 26, 2020 by Editorial Team Author(s): Satsawat Natakarnkitkul Artificial Intelligence, Deep Learning Gentle introduction and implementation of the top three types of ANNs; feed-forward neural networks, RNNs, and CNNs using TensorFlow With the current advancement in data analytic and …
How I Built a Colorectal Cancer Prediction Platform through Deep Learning
Author(s): Adrian Serapio Deep Learning I believe that artificial intelligence can save the human race. How ironic is it though that as any generic sci-fi portrays it, any advanced AI would suddenly conceive the thought that exterminating the human race is the solution …
Unlock the Power of Text Analytics with Natural Language Processing
Author(s): Sharon Lim An insight into Latent Dirichlet Allocation for topic modelling and Naïve Bayes for text classification Continue reading on Towards AI — Multidisciplinary Science Journal » Published via Towards AI …
Visual Representation of Matrix and Vector Operations and implementation in NumPy, Torch, and Tensor
Author(s): Balakrishnakumar V Deep Learning Visual Representation of Matrix and Vector Operations and implementations in NumPy, Torch, and TensorFlow. Implementing rudimentary to advanced operations on deep learning’s fundamental units. Excerpts I am accustomed to creating new deep learning architectures for different problems, …
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