Topics: AI | Data Science | Data Visualization | Deep Learning | Machine Learning | NLP | Python | R | Statistics

About Terence Shin

a data enthusiast with 3+ years of experience in SQL and 2+ years of experience in Python, and a blogger on Towards Data Science and KDnuggets.

Terence Shin Posts (21)

  • Silver BlogHow to be a Data Scientist without a STEM degree - 20 Sep 2021
    Breaking into data science as a professional does require technical skills, a well-honed knack for problem-solving, and a willingness to swim in oceans of data. Maybe you are coming in as a career change or ready to take a new learning path in life--without having previously earned an advanced degree in a STEM field. Follow these tips to find your way into this high-demand and interesting field.
  • 3 Most Important Lessons I’ve Learned 3 Years Into My Data Science Career - 13 Sep 2021
    After only 3 years of working as a data professional, many tried-and-true lessons can be learned. Here are 3 of the most important lessons learned with key takeaways and reflections shared.
  • Rewards BlogGold Blog3 Reasons Why You Should Use Linear Regression Models Instead of Neural Networks - 02 Aug 2021
    While there may always seem to be something new, cool, and shiny in the field of AI/ML, classic statistical methods that leverage machine learning techniques remain powerful and practical for solving many real-world business problems.
  • Gold Blog11 Important Probability Distributions Explained - 20 Jul 2021
    There are many distribution functions considered in statistics and machine learning, which can seem daunting to understand at first. Many are actually closely related, and with these intuitive explanations of the most important probability distributions, you can begin to appreciate the observations of data these distributions communicate.
  • Silver BlogHow to Get Practical Data Science Experience to be Career-Ready - 07 Jul 2021
    Becoming a professional in the field of data science takes more than just book-smarts. You need to have experience with real-world data sets, frequently-used tools, and an intuition for solutions that you can only gain from hands-on experience. These resources will jump start developing your practical skills.
  • Rewards BlogGold BlogHow I Doubled My Income with Data Science and Machine Learning - 01 Jun 2021
    Many career opportunities exist in the ever-expanding domain of data. Finding your place -- and finding your salary -- is largely up to your dedication, focus, and drive to learn. If you are an aspiring Data Scientist or have already started your professional journey, there are multiple strategies for maximizing your earning potential.
  • The Most In Demand Skills for Data Engineers in 2021 - 18 May 2021
    If you are preparing to make a career in data or are looking for opportunities to skill-up in your current data-centric role, then this analysis of in-demand skills for 2021, based on over 17,000 Data Engineer job postings, should offer you a good idea as to which programming languages and software tools are increasing and decreasing in importance.
  • Silver BlogWhy You Should Consider Being a Data Engineer Instead of a Data Scientist - 27 Apr 2021
    A new king of the jungle has emerged.
  • Platinum BlogThe Most In-Demand Skills for Data Scientists in 2021 - 15 Apr 2021
    If you are preparing to make a career as a Data Scientist or are looking for opportunities to skill-up in your current role, this analysis of in-demand skills for 2021, based on over 15,000 Data Scientist job postings, should offer you a good idea as to which programming languages and software tools are increasing and decreasing in importance.
  • Platinum BlogTop 10 Python Libraries Data Scientists should know in 2021 - 24 Mar 2021
    So many Python libraries exist that offer powerful and efficient foundations for supporting your data science work and machine learning model development. While the list may seem overwhelming, there are certain libraries you should focus your time on, as they are some of the most commonly used today.

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