30+ Machine Learning Resources

30+ Machine Learning Resources

  • May 25, 2018
Table of Contents

30+ Machine Learning Resources

For almost all machine learning projects, the main steps of the ideal solution remain same. Briefly, we all go over the steps below each and every time: Understand the dataClean up, fix the missing values, extract new features, select the best onesBuild the model, compare it with the other ones, tune hyper parameters, find out what is the right metric to evaluate your modelIterate this process over and over again until you believe you have the best solution:) Iterate this process over and over again until you believe you have the best solution:)

During each step, I had to do some research on the web depending on my business object and jotted down the best resources I ran across. The resources include Online Courses, Kernels from Kaggle, Cheat Sheets and Blog Posts. Below I’ve listed them and categorised by each step (all of the resources are free except the ones that have ‘paid’ in the end):

Source: medium.com

Tags :
Share :
comments powered by Disqus

Related Posts

Deep Learning Research: Creating Adaptable Meta-Learning Models

Deep Learning Research: Creating Adaptable Meta-Learning Models

Adaptability is one of the key cognitive abilities that defined us as humans. Even as babies, we can intuitively shift between similar tasks even if we don’t have prior training on them. This contrasts with the traditional train-and-test approach of most artificial intelligence(AI) systems which require an agent to go through massive amounts of training before it can master a specific task.

Read More
Intel AI Lab open-sources library for deep learning-driven NLP

Intel AI Lab open-sources library for deep learning-driven NLP

The Intel AI Lab has open-sourced a library for natural language processing to help researchers and developers give conversational agents like chatbots and virtual assistants the smarts necessary to function, such as name entity recognition, intent extraction, and semantic parsing to identify the action a person wants to take from their words. The first-ever conference by Intel for AI developers is being held Wednesday and Thursday, May 23 and 24, at the Palace of Fine Arts in San Francisco. The Intel AI Lab now employs about 40 data scientists and researchers and works with divisions of the company developing products like the nGraph framework and hardware like Nervana Neural Network chips, Liu said.

Read More