Programming is considered a prerequisite to becoming a Data Scientist. A person versed with programming logic, nuances and functions are thought of as having the skills required for a successful career in a data science role.
However, the recent development in tech has ensured that even people who don’t know how to code have a chance at becoming a data scientist. Today, there are tools available that obviate the programming aspect and offers intuitive GUIs (Graphical User Interface) that enables users with minimal knowledge of algorithms to built top-notch ML models. This blog discusses the top 5 GUI driven data science tools.
On another note, those of you who want to get versed in Programming languages can explore the various courses and certifications to quickly escalate into a data science role. You can also gain an in-depth comprehension of the Machine Learning and Data Science by exploring the various courses.
RapidMiner is a software platform for data science that offers an integrated environment for various technological processes including machine learning, deep learning, data preparation, predictive analytics, and data mining. The GUI is very similar to Matlab Simulink and is rooted in a block-diagram approach. In RapidMiner, there are predefined blocks that behave like plug and play devices. Connect it in the right way and a user can run different kinds of algorithms without even one line of code. RapidMiner also enables the user to integrate Python and R scripts into the system.
RapidMiner is used widely in industries such as banking, manufacturing, oil & gas, automotive, life sciences, telecommunication, retail, and insurance. Following are some of RapidMiner’s products that are used commonly deployed:
- RapidMiner Studio: RapidMiner is a stand-alone tool that is used for statistical modeling, data preparation and visualization.
- RapidMiner Server: RapidMiner Server enables computation, deployment, collaboration and thus enhances the productivity of the analytics team.
- RapidMiner Radoop: RapidMiner Radoop is used to enable easy data science in Hadoop and Spark.
- RapidMiner Cloud: RapidMiner is a cloud-based repository that enables easy sharing of information among different tools.
DataRobot is the founder of automated machine learning platform that enables businesses to build predictive models at a fast rate. The brains behind this platform are top Kaggle data scientists – Jeremy Achin, Owen Zhang, and Thomas DeGodoy. With DataRobot, data scientists and analysts regardless of their skill level can deploy machine learning models without even writing a line of code.
Some of the other unique features provided by DataRobot are:
- Model Optimization
DataRobot automatically identifies the best feature engineering and data pre-processing by using text mining, variable type detection, imputation, scaling and encoding. The platform also automatically chooses the hyper-parameters based on the validation set score and error metrics.
- Parallel Processing
In this platform, the computation is divided into thousands of multi-core servers. Also, distributed algorithms are employed to scale to large datasets.
Here, the user can deploy facilities easily with just a click and does not need to write any new code.
- For Software Engineers
In this platform APIs and Python SDK are available which enables fast integration of models into programs and tools.
The fundamental goal of BigML is to make machine learning easy and understandable to everyone. This platform provides a simple interface that enables the user to import their data and get predictions out of it. A remarkable aspect of this service is that it does not expect the user to be well versed in ML technique to reap all the benefits in ML. With it’s powerful ‘1 Click ‘ feature, BigML easily builds predictive models.
This platform also offers a superior result visualization and also has algorithms for solving regression, clustering, anomaly detection, classification and association discovery problems. BigMl has several packages bundled together that are available in a monthly, yearly and quarterly subscription. Users can also avail a free package, however, the size of the dataset they can upload here is just 16MB.
Recently Trifecta was given the epithet of No. 1 Data Preparation Technology by the global technology research firm Ovum for self-service data preparation for 2018-19. Trifecta is a Big Data startup that is primarily known for one thing, that is data wrangling. This startup focuses on enabling data analysts and businesses to analyze, structure and bring together diverse data sources for business purposes. Some of the industries that use Trifecta include telecommunication, life science, and finance industries.
This startup has three products, which are:
- Wrangler, which is a free stand-alone software that allows up to 100MB of data.
- Wrangler Pro, an upgraded version of Wrangler that allows both single and multi-user. It allows data up to 40MB.
- Wrangler Enterprise is the superlative product from Trifecta. Not only does it allow unlimited users, but also does not have any limit on data the user can process. This product is ideal for large organizations.
The GUI provided by Trifecta is intuitive and the best for the data cleaning process. This platform takes data as input and then provides a summary of various statistics by column. It also gives recommendations on the transformation required for each column. That can be accessed by one single. This transformation can be performed on the data easily with the aid of predefined functions which can be called quickly and easily in the interface.
Google introduced Cloud AutoML this year in 2018 to enable individuals with limited expertise in ML to build high-quality ML models. Global organizations such as Disney and Urban Outfitters are already leveraging this product to make their website search and shopping more relevant.
The first product in their CloudAutoML range is Cloud AutoML Vision which is built primarily on Google’s transfer learning and neural architecture search technologies. This product makes it easier to train image recognition models. It provides a drag and drop interface that enables users to upload images, train the model and deploy it directly on Google Cloud.