Making AI More Accessible
Author(s): Elena Marocco Why UX Is a Vital Part of the Success of AI Continue reading on Towards AIβββMultidisciplinary Science Journal Β» Published via Towards AI …
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 humanΒ 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 …
Predicting Heart Failure Survival with Machine Learning ModelsβββPart I
Author(s): Anirudh Chandra A step-by-step pythonic walk-through of the analysis of survival data along with domain-level explanation. Continue reading on Towards AIβββMultidisciplinary Science Journal Β» Published via Towards AI …
Data Validation Framework in Apache Spark for Big Data Migration Workloads
Author(s): Karthikeyan Siva Baskaran Quality Assurance Testing is one of the key areas in Bigdata Continue reading on Towards AIβββMultidisciplinary Science Journal Β» Published via Towards AI …
Calculus in Machine Learning
Author(s): Benjamin Obi Tayo Ph.D. Behind every machine learning model is an optimization algorithm that relies heavily on calculus Continue reading on Towards AIβββMultidisciplinary Science Journal Β» Published via Towards AI …
A Rudimentary Voice Authentication System with Mobile Deployment
Author(s): OngKoonHan Speaker Verification, Android Deployment, Deep Learning, Web Service Continue reading on Towards AIβββMultidisciplinary Science Journal Β» Published via Towards AI …
Easy to use Correlation Feature Selection with Kydavra
Author(s): Vasile PΔpΔluΘΔ Machine Learning Almost every person in data science or Machine Learning knows that one of the easiest ways to find relevant features for predicted value y is to find the features that are most correlated with y. However few …
Inference vs. Prediction
Author(s): Alexandros Zenonos, PhD A lot of people seem to confuse the two terms in the context of machine learning. This post will try to clarify what we mean by the twoβ¦ Continue reading on Towards AIβββMultidisciplinary Science Journal Β» Published via …
Unsupervised vs. Supervised Learning
Author(s): Rajaram VR Machine Learning I just started my initial steps into data science and machine learning, and, got introduced to βSupervised Learningβ techniques as βClassifiers (Decisiontreeclassifer from sklearn kit), and on the unsupervised learning, with βClustering.β In this case, we are …
Random Stock GeneratorβββMonte Carlo Simulations in Finance
Author(s): Michelangiolo Mazzeschi Learn how to generate n procedural stocks. Full code available at my repo. Continue reading on Towards AIβββMultidisciplinary Science Journal Β» Published via Towards AI …
Tips for Effective Technical Blogging
Author(s): Kurtis Pykes What Iβve Learnt from 8 Months of Consistent Writing Continue reading on Towards AIβββMultidisciplinary Science Journal Β» Published via Towards AI …
Data Ingestion from 5 Major Data Sources using Python
Author(s): Manmohan Singh Learn, why data stored in different sources, and how you retrieve them using python? Continue reading on Towards AIβββMultidisciplinary Science Journal Β» Published via Towards AI …
Unlock the Power of Text Analytics with Natural Language Processing
Author(s): Sharon Lim An insight into Latent Dirichlet Allocation for topic modelling and NaΓ―ve Bayes for text classification Continue reading on Towards AIβββMultidisciplinary Science Journal Β» Published via Towards AI …
PopTheBubbleβββA Product Idea
Author(s): Sanghamesh Vastrad A Product Managerβs Perspective on building a Crowdsourced Media Bias Tracker and Anonymous Political News Aggregator Photo by airfocus onΒ Unsplash A couple of months ago, I decided to try something new. The MVP Lab by Mozilla is an 8-week …
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 learningβs fundamental units. Excerpts I am accustomed to creating new deep learning architectures for different problems, …
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