Automated Machine Learning Software/ Tools: In depth Guide

We explained autoML in detail. Now it is time to figure out the right software for auto ML for your business.

3 Types of AutoML Solution Providers

Open Source

AI is one of the few scientific areas were despite significant corporate investment, even secretive tech giants like Apple publish their research findings. Therefore it should not be surprising that there are competitive open source autoML tools.

All open source tools we came across, need an active development environment in Python or R and require the user to write at least a few lines of code to initiate the automated machine learning process. Read more

Share

Automated Machine Learning: In depth Guide [2018]

Automated machine learning has the potential to greatly increase the productivity of data scientist and democratize machine learning tools. It can be a powerful solution to the well documented scarcity of data scientists.

What is automated machine learning?

According to Wikipedia:

Automated machine learning (AutoML) is the process of automating the end-to-end process of applying machine learning to real-world problems.

Automated ML solutions aim to automate some or all steps of the machine learning process which includes:

  • Data pre-processing
  • Feature engineering
  • Feature extraction
  • Feature selection
  • Algorithm selection & hyperparameter optimization

Since accuracy of machine learning solutions can be measured, automated systems can fine-tune data, features, algorithms and hyperparameters of algorithms to generate accurate models relying on established machine learning knowledge and trial&error. Read more

Share

AI talent war: Struggle to attract top AI leaders [2018]

We set out to quantify the efforts of companies to attract top AI leaders and companies.

Company acquisitions

CBInsights prepared this excellent infographic on large tech’s AI company acquisitions:

CBInsights

Personnel acquisitions

Apple hired Google’s head of search and AI

It’s impossible to make a complete list on this topic but feel free to contribute other significant developments on the AI talent war.

Share

Top 12 Benefits of Chatbots: Comprehensive Guide [2018 update]

No one can know benefits of chatbots better than potential users of chatbots. So that’s where we started, the above list is based on Drift’s 2018 State of Chatbots Report. We added a few more points to categorize benefits of chatbots clearly.

Benefits to Customers

  • 1- 24 hour availability: While this is clearly a huge benefit, highlighting this risks creating backlash when bots are down due to security issues or maintenance
  • 2- Instant answers
  • 3- Consistent answers: Talking to a customer service rep, a customer has no assurance that other reps are also providing similar, consistent responses. If a customer service rep is not helpful, a customer could be tempted to try calling again to see if the next rep is better.
  • 4- Recorded answers: Talking to a customer service rep, a customer gets no record of the conversation and most people would prefer not to record their conversations. However, a customer can take a screenshot whenever she likes, to remember the conversation or to challenge an answer provided by the bot.
  • 5- Instant transactions: Actions like changing or querying records are almost instantaneous for bots.
  • 6- Endless patience: While customer reps and customers sometimes lose their patience, that’s something bots are yet incapable of.
  • 7- Programmability: Since bots are on digital platforms where people spend majority of their waking hours working, bots can be used to automate common tasks such as arranging meetings, providing advanced search functionality

Benefits to Companies Read more

Share

In-depth Sales Analytics Guide: Best Practices, Applications [2018]

Unlike marketing, sales has always been numbers driven and now with the explosion of data and computational power, sales analytics has become central to any large sales organization

What is sales analytics?

Sales involves making many decisions with limited data. Sales analytics helps uncover insights and increasingly recommends the best decisons to sales reps and managers.

Source: HBR

Relevant data sources include most data used by marketing departments such as account level and lead level digital history and preferences along with rich data on all sales rep interactions such as calls logs and emails. Read more

Share