Data science and machine learning are two of the hottest industries these days. Every fresh IT graduate wants to make a career in data science or machine learning. With tech giants and big brands pouring in millions of dollars in research and development in both data science and machine learning, it is obvious why there is so much hoopla surrounding these two industries.
With data being the new fuel for businesses, you need BI tools which can help you take full advantage of these huge data sets by extracting valuable information from it. You would also need data scientists and machine-learning specialists, who would be able to navigate these tools. This leaves out non-technical people who don’t have programming skills and technical know-how about how these tools work. Thankfully, there are a few data science and machine learning tools that even a beginner with barely any knowledge or experience in programming, can use.
In this article, we will highlight some of these tools so you can make the most of data at your disposal.
1. DataRobot
DataRobot is an automated machine learning platform built by some of the best in the industry. Such as Jeremy Achin, Thoman DeGodoy, and Owen Zhang. What makes this tool great is that it eliminates the need to hire a data scientist.
Here is what its website says, “Data science requires math and stats aptitude, programming skills, and business knowledge. With DataRobot, you bring the business knowledge and data, and our cutting-edge automation takes care of the rest.” From model optimization to parallel processing to deployment, you can do it all with DataRobot.
Thanks to the use of text mining, imputation, variable type detection, scaling and transformation, DataRobot automatically detects the best data processing and feature set. Even hyper-parameters are automatically selected based on validation set score and error metric. With thousands of powerful servers, parallel processing is a possibility. In addition to this, scaling to large data sets is no longer difficult, thanks to distributed algorithms.
2. Tableau
Tableau Public is by far the most popular visualization tool on the market today. It lets you create graphs, maps, charts with fewer clicks as possible. What is even better is that it is free to use. As with most software, the free version is quite limited in functionality. But if you want to make the most of your data, it is highly recommended that you invest in the premium version of Tableau.
3. Datawrapper
Datawrapper is a digital tool that makes creating interactive visuals of data a breeze. Generating any type of visualization from your data is now possible with Datawrapper. You can either represent your data in the form of a line graph, bar graph or interactive charts. Many news channels and organizations to represent data in an interesting manner have used Datawrapper. This speaks volumes about its credentials. If you want to deliver a presentation or submit a quarterly report, Data wrapper might be your best friend.
4. Rapid Miner
What started as an open source tool back in 2006 became one of the best data mining tools in 2018. The journey has been fascinating for RapidMiner. For those who like to tinker with coding and software, RapidMiner’s older versions, i.e. below version 6, are still open source. But if you want to experience the latest version, there would be a free 14-day trial followed by a premium license you will have to buy a subscription.
What makes RapidMiner one of the best in its class, is its complete coverage of each stage of prediction modeling from data preparation to data validation and deployment. If you have ever used Matlab Simulink, you will feel right at home with its block diagram like user interface. You can execute dozens of algorithms without the need of writing a single line of code.
The RapidMiner server fosters team collaboration, makes project management easier and makes model deployment easier. It also makes big data analytics simpler with RapidMiner Hadoop. There is a cloud-based repository and a standalone software called RapidMiner Cloud and RapidMiner Studio, which make data preparation and visualization, as well as modeling, a hassle-free experience for users.
5. Fusioo
Fusioo is a database application for the masses. It is a simple and easy to use interface and is a delight to use even for a beginner without any idea of using database software. Throw in its excellent collaboration and reporting tools and you get the database software you have long been waiting for. There is also an option, which lets users invite clients or external collaborators without paying a penny. If you want to dive into data without the need of writing any code then, Fusioo will surely put a smile on your face.
6. BigML
BigML is a machine-learning platform that takes the user through a step-by-step process. It begins with sources, datasets, models and ends with predictions, ensembles, and evaluation. Solving machine-learning problems such as classification, regression, association, clustering, and discovery is no longer an issue, thanks to wide range of BigML algorithms. Want to see how it works? Check out their YouTube channel or watch this video.
7. Google Cloud Prediction API
Creating machine-learning models for Android application was considered out of question but not anymore because Google has released an API for it. Google’s Cloud Prediction API that lets developers design machine learning models for their Android apps. Its recommendation engine offers accurate recommendations by analyzing user habits and preferences.
With its powerful sentimental analysis capabilities, you can easily analyze the comments about your products or services on social media and categorize them as negative and positive. Additionally, businesses can use this API to predict how much a user is willing to spend on their next purchase by analyzing the purchase history. You can use this API with any popular programming language. For advanced developers, there is also specific Google API client libraries and reap the benefits of blazing fast performance and foolproof security.
Which data science and machine-learning tool is your favorite? Feel free to share it with us in the comments section below.
