Google Stock prediction using Multivariate LSTM
Author(s): Michelangiolo Mazzeschi Using a Vanilla LSTM to predict Google Stock prices Continue reading on Towards AIβββMultidisciplinary Science Journal Β» Published via Towards AI …
Mythbusting 5G
Author(s): Jasper Ruijs — A thoughtful overview of the heated debate Continue reading on Towards AIβββMultidisciplinary Science Journal Β» Published via Towards AI …
NLP News Cypher | 07.26.20
Author(s): Ricky Costa Originally published on Towards AI. Photo by Will Truettner on Unsplash NATURAL LANGUAGE PROCESSING (NLP) WEEKLY NEWSLETTER NLP News Cypher U+007C 07.26.20 Primus The Liber Primus is unsolved to this day. A book of 58 pages written in Runes, …
NLP News Cypher | 07.26.20
Author(s): Quantum Stat Photo by Will Truettner onΒ Unsplash NATURAL LANGUAGE PROCESSING (NLP) WEEKLY NEWSLETTER Primus The Liber Primus is unsolved to this day. A book of 58 pages written in Runes, of which, its bewildering encryption continues to haunt hacker gunslingers around …
Digit Classification using Tensorflow, Keras
Author(s): Michelangiolo Mazzeschi Full code available at my repo. Sources at this link. Continue reading on Towards AIβββMultidisciplinary Science Journal Β» Published via Towards AI …
Why do We Need Activation Functions in Neural Networks?
Author(s): Dorian Lazar Activation functions motivated by examples Continue reading on Towards AIβββMultidisciplinary Science Journal Β» Published via Towards AI …
Building a super-resolution image web-app
Author(s): Aanisha Bhattacharyya This is a web-app trained on SRCNN model. On giving an image as input, it reconstructs a higher resolution image of the same. I made this… Continue reading on Towards AIβββMultidisciplinary Science Journal Β» Published via Towards AI …
Deep Insights Into K-nearest Neighbors
Author(s): Palak Machine Learning Photo by ZdenΔk MachΓ‘Δek onΒ Unsplash Introduction K-nearest neighbors(in short KNNs) are a robust yet straightforward supervised machine learning algorithm. Though its regression variant also exists, weβll only discuss its classification form. KNN is a non-parametric lazy learning algorithm. …
These Data Science Skills will be your Superpower
Author(s): Benjamin Obi Tayo Ph.D. 10 Essential Skills You Need to Know to Start Doing Data Science Continue reading on Towards AIβββMultidisciplinary Science Journal Β» Published via Towards AI …
Predictive Modeling in Healthcare Analytics
Author(s): Saiteja Kura Let us understand how to build a good predictive model in healthcare systems. Continue reading on Towards AIβββMultidisciplinary Science Journal Β» Published via Towards AI …
Introduction
Author(s): Palak Originally published on Towards AI. Intuitive Approach Photo by ZdenΔk MachΓ‘Δek on Unsplash K-nearest neighbors(in short KNNs) are a robust yet straightforward supervised machine learning algorithm. Though its regression variant also exists, weβll only discuss its classification form. KNN is …
Introduction
Author(s): Odemakinde Elisha Originally published on Towards AI. Data Analytics, Machine Learning Utilization of Dask ML Framework for Fraud Detection βEnd-to-end Data Analytics Photo by Michael Longmire on Unsplash Fraudulent activities have become a rampant activity that has aroused a lot of …
Convolutional Neural Networks for Dummies
Author(s): Daksh Trehan Deep Learning, ComputerΒ Vision A perfect guide to Convolution NeuralΒ Networks A notification pops on your Social media handle saying, somebody uploaded a picture that might have you inΒ it. Boom! How did itΒ happen? Photo by Patrick Fore onΒ Unsplash This is the …
Data Visualization using Pandas, NumPy, and Matplotlib Python Libraries
Author(s): Likhitha kakanuru Originally published on Towards AI. Data Visualization To analyze which students secured the highest percentage in subjects like mathematics, physics, and chemistry we require a bar graph to display it. There are many ways to explore datasets. But in …
Time Series Prediction using Adaptive Filtering
Author(s): Satsawat Natakarnkitkul Originally published on Towards AI. Simple implementation example Adaptive filtering is a computational device that attempts to model the relationship between two signals, whose coefficients change with an objective to make the filter converge to an optimal state. The …
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