AutoML refers to techniques for automatically discovering the best-performing model for a given dataset. When applied to neural networks, this…

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## The Value of Data Now vs. Data Later

Since 1965, the tech industry has considered Moore’s Law the defining trajectory of big data. Microchips have since become more…

Continue Reading## Andre Ye

Machine Learning for Biology: How Will COVID-19 Mutate Next?Genome sequence analysis with K-Means &…Matrix Factorization as a Recommender SystemAn Explanation and Implementation…

Continue Reading## Demystifying the Mathematics Behind Convolutional Neural Networks (CNNs)

Overview Convolutional neural networks (CNNs) are all the rage in the deep learning and computer vision community How does this…

Continue Reading## Who is the Best IPL Batsman to Bat with? Finding the Answer with Network Analysis

Introduction Did you know that the Indian cricket team relies heavily on data analytics to decide their strategy for an…

Continue Reading## How to Develop a Cost-Sensitive Neural Network for Imbalanced Classification

Deep learning neural networks are a flexible class of machine learning algorithms that perform well on a wide range of…

Continue Reading## Applying Occam’s razor to Deep Learning

By Mehmet Suzen, Theoretical Physicist, Research Scientist. Occams razor or principle of parsimony has been the guiding principle in statistical model…

Continue Reading## Considerations for Effective AI in Mobile Networks

It’s a subject of ongoing research, but comes down to the robustness of the system. A robust system needs to…

Continue Reading## David Gündisch

Writing your first Generative Adversarial Network with Keras. How to beat facial recognition systems with Face Anonymization. Writing your first Neural…

Continue Reading## Matthew Stewart, PhD Researcher

Guide to R and Python in a Single Jupyter NotebookAdvanced Topics in Neural NetworksAn introduction to some advanced neural network topics such as…The…

Continue Reading## Recurrent Neural Networks (RNNs)

Recurrent Neural Networks (RNNs)Implementing an RNN from scratch in Python. Javaid NabiBlockedUnblockFollowFollowingJul 11The main objective of this post is to implement an…

Continue Reading## Gaining insights on transfer learning with FlashTorch

If you’ve done the maths already… I would be better of randomly guessing it myself. Intuitively, this perhaps makes sense.…

Continue Reading## Fashion product image classification using Neural Networks | Machine Learning from Scratch (Part VI)

The prediction is correct!Classifying ImagesBuilding a Neural NetworkOur Neural Network will have only 1 hidden layer. We will implement a somewhat…

Continue Reading## Neural Network Optimization

Neural Network OptimizationCovering optimizers, momentum, adaptive learning rates, batch normalization, and more. Matthew Stewart, PhD ResearcherBlockedUnblockFollowFollowingJun 27“The goal is to hit…

Continue Reading## Neural Networks with push button, AI for all

Neural Networks with push button, AI for allNeural Architecture Search with NASBench from Google Research— Can we design network architectures automatically,…

Continue Reading## Do Conv-nets Dream of Psychedelic Sheep?

By Kevin Vu, Exxact Corp. Deep dreaming at successive layers of abstraction. From top to bottom: input image, conv2-3x3_reduce, inception_4c-1×1.…

Continue Reading## LSTM: How To Train Neural Networks to Write like Lovecraft

I’ll explain it now, though I highly recommend you give those tutorials a chance too. How do LSTM cells work?An LSTM…

Continue Reading## Improving Deep Neural Networks

Improving Deep Neural NetworksRochak AgrawalBlockedUnblockFollowFollowingJun 19Deep Neural Networks are the solution to complex tasks like Natural Language Processing, Computer Vision, Speech…

Continue Reading## Classification Using Neural Networks

After reading this article you should have a rough understanding of the internal mechanics of neural nets, and convolution neural…

Continue Reading## Layman’s Introduction to Backpropagation

Layman’s Introduction to BackpropagationTraining a neural network is no easy feat but it can be simple to understand itRishi SidhuBlockedUnblockFollowFollowingJun…

Continue Reading## The Basics of Neural Networks with Tensorflow

The Basics of Neural Networks with TensorflowChristopher KazakisBlockedUnblockFollowFollowingJun 5Today, we’re going to learn the basic ideas behind how a neural…

Continue Reading## CNN Heat Maps: Class Activation Mapping (CAM)

CNN Heat Maps: Class Activation Mapping (CAM)Rachel Lea Ballantyne DraelosBlockedUnblockFollowFollowingJun 11This is the first post in an upcoming series about different…

Continue Reading## Network Science & Threat Intelligence with Python: Network Analysis of Threat Actors/Malware Strains (Part 1)

And more specifically, threat intelligence?Well, we plot hundreds and thousands of attributes and relationships within threat intelligence. The amount of…

Continue Reading## Step-by-step understanding LSTM Autoencoder layers

Step-by-step understanding LSTM Autoencoder layersHere we will break down an LSTM autoencoder network to understand them layer-by-layer. We will go…

Continue Reading## Knowing Your Neighbours: Machine Learning on Graphs

We can broadly classify the kinds of problems connected data can solve into four categories:Node ClassificationLink PredictionCommunity DetectionGraph ClassificationThere exist…

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