Collab & Grow Your Knowledge on these Data Science Networking Platforms

Collab & Grow Your Knowledge on these Data Science Networking Platforms
Published on

Networking platforms for you to meet fellow data science peers.

Data science and machine learning, have rapidly surged in popularity. The trend of aspirants and tech enthusiasts has spiked in 2021 and more options in this field are being explored. Because data science has become such a lucrative field, everyone is eager to learn about the latest developments and skills that are needed to enter this tech field.

For beginners and experts, Analytics Insight has discovered some data science communities to add some additional knowledge and ace the job. For beginners, it is important to have strong foundation skills and know all about the right tools and solutions. For experienced professionals, knowing the latest programming languages and trends is crucial as data science is such a tech field that demands constant learning.

These networking websites bring a wholesome mix of interaction with fellow data science professionals and enthusiasts and data science experts who will help you understand the field in-depth.

LinkedIn: LinkedIn is a renowned professional networking website that doesn't just help people get jobs but also connects them with fellow peers of their field and beyond. As you are looking for data science resources, you can connect with several data scientists and analysts, discover their blogs, interact with them to share knowledge, and discover opportunities. There are several data science communities on LinkedIn that are dedicated to specific subjects like Python and machine learning Hadoop. All you have to do is get on the search bar and use data science as the keyword.

Data Science Reddit: If you thought Reddit is just for memes, hobbies, and fanfics, think again. But Reddit is a social networking platform where professionals can connect more freely. There are plenty of resources on Reddit about data science and machine learning such as r/datascience, r/dataisbeautiful, r/machinelearning, and r/dataforgeeks. While r/datascience is for beginners, r/machinelearning is for professionals who want to discuss problems on an anonymous network.

Kaggle: This Google-owned platform is the largest data science community online. Kaggle was originally built as a tool to gather teams for competitions but it now allows users to publish data sets, explore, and share data-science-related work with their peers. You can also participate in beginner, advanced, and expert-level data science competitions and win cash prizes for your skills. Kaggle also provides free access to Nvidia K80 GPU kernels. This will give you a 12.5X speed boost to train a deep learning model.

IBM Data Science Community: IBM Data Science community is one of the best resources out there for everyone in this field. If you are looking for expert-level insight for crucial data science challenges, there is no better platform. You will see experts from top tech companies blogging, podcasting, and answering user questions on this platform. If you want specific guidance from an industry expert, you can interact with them and join other communities to share your knowledge.

Stack Exchange: Stack Exchange has many diverse communities on various tech topics, data science being one of them. You will see developers discussing web frameworks, AI engineers talking about ethics, and data analysts discussing ML tools. These days, many data science professionals are required to know to code, so if you have any coding doubts or need help in building a model, you can connect with an expert to get your doubt rectified or hire a developer to build software for you.

Join our WhatsApp Channel to get the latest news, exclusives and videos on WhatsApp

                                                                                                       _____________                                             

Disclaimer: Analytics Insight does not provide financial advice or guidance. Also note that the cryptocurrencies mentioned/listed on the website could potentially be scams, i.e. designed to induce you to invest financial resources that may be lost forever and not be recoverable once investments are made. You are responsible for conducting your own research (DYOR) before making any investments. Read more here.

Related Stories

No stories found.
logo
Analytics Insight
www.analyticsinsight.net