Why MachineHack is the Best Platform for Data Scientists
If you are a developer and you want to share your coding skills, you will have to share your GitHub profile. If you are a writer, you have to share your medium profile. If you are good at Hackathons, you have to prove it with your Kaggle profile. But what if all this can be combined in a single overarching platform? Launched in 2018, MachineHack is the perfect platform offering a bouquet of options for people who are doing data engineering, data science, machine learning, or development, from an early to an experienced practitioner and are willing to solve real-world problems. You can come on this platform to upskill yourself, assess where you stand in the crowd, write articles, learn coding, apply for jobs, and also build an outstanding portfolio! The community has more than 100K+ registered developers, and has hosted around 100 hackathons till date, and provided job opportunities to more than 1000 developers. One of the unique features of MachineHack is the Interview Prep section which has ready-to-take MCQ questionnaires to quickly gauge your skills. It is divided into three categories: ML Skills: The skills sections cover niche, specific topics like computer vision, natural language processing, and cloud technologies among many others. Popular Job Roles: This section has mock interviews for specific job roles like ML engineer, Data Engineer, Data Scientist and more, which also include preparations for individual roles at companies like Google, Microsoft, AWS, and others. Exam Preparation: This section includes mock tests and exams for certification courses and programmes. Most of the courses available on the website are free but select in-depth and unique courses require a premium subscription. You also earn MH points each time you visit a page or a particular course, which you can redeem for the premium membership once collected. Read: 9 Platforms for Building a Strong Data Science Portfolio Hackathon As the name suggests, MachineHack’s favourite part is the Hackathon, which is simultaneously the crux of the platform. With parallelly running Hackathons and challenges, data scientists and engineers can verify their stance in the field and compete with others to grow further and win prizes reaching up to thousands of dollars along the way. The MachineHack team provides a training dataset of a specific problem along with a testing dataset. The participants have to build and train the model and assess the accuracy on that specific dataset, proving the efficiency and performance of the model. This submitted model is then scored by MachineHack’s expert team and awarded accordingly. Another section under Hackathon is Blogathons for people pursuing their career in machine learning writing. One of the current running blogathons is The Ultimate Samur-AI Writer Blog-A-Thon for NLP-based content. MachineHack also partners with companies to host their hackathons on the platform. Competing in these Hackathons can definitely get you noticed and also help you land a job in the data science and machine learning field. Not just for writing or making models, MachineHack also holds Data Visualisation Competitions, wherein data engineers can participate and use tools like PowerBI, Tableau, or DataWrapper to create graphs and charts to form a visual representation of the given data. Read: Top Data Science Hackathon Platforms with Active Challenges Practice For a coder or programmer, the idea and criteria to analyse is not how you write the code, but how optimised code you can write, which means the model should use minimum CPU and minimum memory. It is measured in OPS (Operations per Second), measuring how many operations can be performed within a second. With the Practice section, developers and coders can try solving problems available on the website and submit it to check how good of a coder they are and eventually increase their skills. Coders can choose from 1000+ topics from the list and submit their responses multiple times for assessment. The code is checked online in real-time and the results are displayed immediately. The topics are listed for beginners, advanced, and intermediate—offering a plethora of choices for every stage of developer. Along with this, you can also see your ranking and where you stand among all the people who have attempted to solve the problem by seeing their runtime and errors, though the code itself is not shared. Courses To learn about machine learning and data science, there are plenty of places to try like YouTube, Vimeo, or edX, but the problem is that the length of these courses are sometimes more than 3–4 months since they cover all the topics of a field. Even Coursera offers certificates but the courses take a lot of time to complete. MachineHack has a unique Courses section, which includes around 100 niche courses of machine learning. These courses are short and talk about a specific topic in machine learning. If you are preparing for an interview and want to quickly revise a certain topic, these courses will refresh your memory in a span of 30 minutes with theory, hands-on, and videos. This offering is exclusively available on MachineHack that creates a separate server for each developer and generates a unique code which can be changed and built for a different output. The whole notebook is integrated on the website and provides developers with an end-to-end platform to test and practise a niche topic within a given time period. Read: 14 Best YouTube Channels for Data Science and Machine Learning Discussions To create a stack overflow for machine learning and data science engineers, MachineHack has a dedicated community of developers where people can post questions, from very broad to very specific topics, and discuss the answers in the community. This space is actively operating and developers can post errors they face directly in the general questions section and discuss with team experts. Read: 15 Data Science Projects that Will Land You a Job in 2023 Events You can revisit the events you missed out on in this section. It has videos of conferences, seminars, and workshops curated by experts—all available for free to every user. The videos are also filtered on the basis of the speaker, events, companies, and topics. Jobs Now that you have all these sections where you can learn, compete, and discuss ideas, MachineHack also has a Job section where you can search and apply for jobs that are regularly updated. AIM Recruits is actively uploading jobs on the server and companies like Microsoft, Intel, and many others also post their jobs here directly. Read: Best Websites to Scout for Remote Data Science Jobs Blogs The latest offering of MachineHack allows developers to publish their blogs and reach a larger audience. Writers interested in machine learning, data science, or artificial intelligence, can contribute their blogs on this section and the MachineHack team will review it before publishing. It is a great way to reach out to more people and create an industry presence! Additionally, MachineHack recently launched their Wordle that has now crossed 100 players. You can try the latest challenge of the MH Wordle here. Read: Top 9 Platforms to Publish Your Data Science Blogs
The community has more than 100K+ registered developers, and has hosted around 100 hackathons till date, and provided job opportunities to more than 1000 developers.
The community has more than 100K+ registered developers, and has hosted around 100 hackathons till date, and provided job opportunities to more than 1000 developers.
["Courses", "Data Science blogs", "data science projects", "Hackathons", "Machine Hack", "Machinehack"]
["data science projects", "data science", "artificial intelligence", "machine learning", "AWS", "Machinehack", "AI", "TPU", "ML", "Hackathons", "computer vision", "NLP", "Machine Hack", "Aim", "Courses", "Data Science blogs"]
["AI", "artificial intelligence", "machine learning", "ML", "NLP", "computer vision", "data science", "Aim", "AWS", "TPU"]
Mohit writes about AI in simple, explainable, and often funny words. He's especially passionate about chatting with those building AI for Bharat, with the occasional detour into AGI.