But major universities, in particular, can have decent job fairs. However, my real recommendation is that networking events and meetups…

Continue Reading# Machine Learning news

## Turning IT Upside Down In a Machine Learning World

As the legend goes, cows tend to take the path of least resistance from point A to point B and…

Continue Reading## Deployed your Machine Learning Model? Here’s What you Need to Know About Post-Production Monitoring

The next best thing to do is to continuously track the health of the machine learning model against a set…

Continue Reading## Training a Machine Learning Engineer

Once a clear understanding of the problem is established, design the architecture based on the theory youve learnt. I would…

Continue Reading## A Gentle Introduction to Bayes Theorem for Machine Learning

Bayes Theorem provides a principled way for calculating a conditional probability. It is a deceptively simple calculation, although it can…

Continue Reading## Probability for Machine Learning (7-Day Mini-Course)

This is called the “Boy or Girl Problem” and is one of many common toy problems for practicing probability. Post…

Continue Reading## Data Mapping Using Machine Learning

From small to large businesses, just about every company is fighting for a chance to get their audiences attention.…

Continue Reading## Continuous Probability Distributions for Machine Learning

The probability for a continuous random variable can be summarized with a continuous probability distribution. Continuous probability distributions are encountered…

Continue Reading## 5 Beginner Friendly Steps to Learn Machine Learning and Data Science with Python

I put together a couple of steps in the reply and I’m copying them here. You can consider them a…

Continue Reading## Discrete Probability Distributions for Machine Learning

The probability for a discrete random variable can be summarized with a discrete probability distribution. Discrete probability distributions are used…

Continue Reading## Best of arXiv.org for AI, Machine Learning, and Deep Learning – August 2019

A Probabilistic Representation of Deep Learning This paper introduces a novel probabilistic representation of deep learning, which provides an explicit…

Continue Reading## Productionizing Machine Learning: From Deployment to Drift Detection

Try this notebook to reproduce the steps outlined below and watch our on-demand webinar to learn more. In many articles and…

Continue Reading## HPE Accelerates Artificial Intelligence Innovation with Enterprise-grade Solution for Managing Entire Machine Learning Lifecycle

Hewlett Packard Enterprise (HPE) announced a container-based software solution, HPE ML Ops, to support the entire machine learning model lifecycle…

Continue Reading## A Gentle Introduction to Uncertainty in Machine Learning

Applied machine learning requires managing uncertainty. There are many sources of uncertainty in a machine learning project, including variance in…

Continue Reading## Monitor Medical Device Data with Machine Learning using Delta Lake, Keras and MLflow: On-Demand Webinar and FAQs now available!

On August 20th, our team hosted a live webinar—Automated Monitoring of Medical Device Data with Data Science—with Frank Austin Nothaft,…

Continue Reading## 5 Reasons to Learn Probability for Machine Learning

Probability is a field of mathematics that quantifies uncertainty. It is undeniably a pillar of the field of machine learning,…

Continue Reading## Common Machine Learning Obstacles

Sponsored Post. By Seth DeLand, Product Marketing Manager, Data Analytics, MathWorksEngineers and scientists who are modeling with machine learning…

Continue Reading## Resources for Getting Started With Probability in Machine Learning

Machine Learning is a field of computer science concerned with developing systems that can learn from data. Like statistics and…

Continue Reading## Automated Machine Learning: Just How Much?

Some say it can, some say it can’t. In my opinion, automated machine learning can fully automate the Data Science…

Continue Reading## Advice on building a machine learning career and reading research papers by Prof. Andrew Ng

By Mohamed Ali Habib, Computer Science Graduate Since you’re reading this blog, you probably already know who is Andrew Ng, one…

Continue Reading## 6 Tips for Building a Training Data Strategy for Machine Learning

By Wilson Pang, CTO, Appen. Artificial intelligence (AI) and machine learning (ML) are frequently used terms these days. AI refers…

Continue Reading## Here are 7 Data Science Projects on GitHub to Showcase your Machine Learning Skills!

These are critical questions a data scientist needs to answer. And the HungaBunga project will help you reach that answer…

Continue Reading## Growth in Machine Learning: Accessibility of MLaaS and the Future of the Industry

Machine Learning as a Service, or MLaaS, is completely breaking down barriers and has the potential to completely change the…

Continue Reading## Types of Bias in Machine Learning

In one my previous posts I talke about the biases that are to be expected in machine learning and can…

Continue Reading## Best of arXiv.org for AI, Machine Learning, and Deep Learning – July 2019

Sparse Networks from Scratch: Faster Training without Losing Performance This paper demonstrates the possibility of what is called sparse learning:…

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