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Tom Robertson

Tom Robertson
Tom Robertson
Data Science Enthusiast

Tom Robertson is a Python-based data scientist with domain knowledge in behavioral neuroscience research and non-profit development. He is currently employeed as Data Science Instructor at QuickStart Technologies. Tom is inspired by the belief that data science can improve quality of life by providing our researchers, doctors and policy-makers with new, data-driven insights.

Tom has expertise on Python, SQL, and Spark. He has worked on several libraries including but not limited to Scikit-learn, Pandas, NumPy, Matplotlib, Seaborn, SciPy, NLTK, Keras, and Tensorflow.

  1. Top 10 Data Science Influencers

    Top 10 Data Science Influencers

    Categories: Data Science
    We live in an era where modern technologies are the buzzwords everyone talks about. Technologies like data science, artificial intelligence, and machine learning are being discussed even if people are not fully aware of them. Well, that is a positive sign to go with, right? People from non-technical backgrounds seem to misunderstand these technologies the most. If we put them in simple words when we try to simulate human brain functions by a robot or machine, is called artificial intelligence. The ability to learn as the name implies, but from the environment itself and without any kind of programming. And now, the hottest topic of today's world data science. We all are well aware of data, but do we know what and what we can do using data? Well no worries, as data science is here to save the day. Data science is the techniques and practices that help us find the real value of data, the sense that matters for us.  Statistics, mathematics, and data analytics all the methods are applied in this process.
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  2. Data Analysis And Data Science With Python And Pandas

    Data Analysis And Data Science With Python And Pandas

    Categories: Data Science, Data analysis and visualization
    While there are such a significant number of languages out there, Python is an unquestionable requirement to get the hang of programming language for the experts working in the Data Science area. There is an expanded interest for talented Data Scientists in the IT business, and Python has developed as the most favored programming language. With the assistance of this instructional exercise on Python for Data Science, you will comprehend why Python is viewed as the most favored language. Presently, how about we view the essential highlights of Python and its area situations. Many aspiring data scientists start to learn Python by taking programming courses implied for developers.
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  3. Data Scientists Salary Trends

    Data Scientists Salary Trends; 2020 Edition

    Categories: Data Science, Career Driven

    Anyone who is interested in pursuing a career in the field of data science, needs to be clear on things first. You might be a fresh graduate having successfully acquired a Data Science certification to supplement your current skills, or you might be one of those adventurous spirits who wants to take on a challenge and switch your career into the ever-evolving field of Data science. Whatever the case, there are good chances for you to fit right in and be on track to becoming more successful than you were before starting out on this career path. The current economy is one that has ever growing opportunities for data scientists, especially in the US.

    Before we get into the data science salary trends, let us talk briefly about what is data science and more importantly what does a data scientist do?

    Data scientist—A remarkable career?

    From Data you derive information, and from information you derive knowledge. And as the old saying g

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  4. How To Become A Data Analyst

    How To Become A Data Analyst

    Categories: Data Science
    So you're thinking to turn into a data analyst? Kudos to you! You've picked a fulfilling, geographically versatile, and super-secure career in a field that is simply going to continue sprouting in the years to come. Clearly, you should do the immediate front work of learning and sharpening the imperative skills before you can reap the rewards. Follow this broad manual on how to become an ultra-hirable data analyst.
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  5. Why Data Science Teams Need Generalists, Not Specialists

    Why Data Science Teams Need Generalists, Not Specialists

    Categories: Data Science
    Must have heard about big data, right? The time when big data entered our life, we got to know about the importance of data. We had an unlimited amount of data even before big data, but it was the way it was, and we had no idea what to do with it. We did not even have storage space for this enormous volume of data. When big data entered the market, everyone was worried about how to store the data, and every company started working on designing solutions for data storage. After some time and endless efforts, we were able to build Hadoop and other frameworks for storage.
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  6. Data Science Project Management Methodologies

    Data Science Project Management Methodologies

    Categories: Data Science
    Big data is need of time, the requirement for its storage has likewise developed. It was the primary concern and a big challenge for business enterprises until 2010. The fundamental center of attention was on building structure and responses for storing information. Presently when Hadoop and different frameworks have effectively tackled the issue of capacity, the focus has moved to the management of this data.
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  7. How Can Project Managers Use Data Science

    How Can Project Managers Use Data Science

    Categories: Data Science
    Technological advancement has been a lot riveting since the past few years and it has been booming ever since. Data science plays a major role in the prediction of future data by extracting vital information from raw data with the help of special skills of machine learning and other enthralling algorithms, and tools. Data science reveal the buried patterns in the researched data from various enterprises and mold it into a new model illuminating certain quintessential conclusions.
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  8. How to Successfully Manage a Data Science Project

    How to Successfully Manage a Data Science Project

    Categories: Data Science, Project Management
    As there is quintessential technological progress in the world, data storage is becoming a booming hurdle in the main field. However, Hadoop and some other indispensable frameworks have been sufficiently used for the proper storage of the data. When the data storage problem is solved, there erupted another obstacle in the field of technology and that has been the processing of the data. Data Science can be referred to as the main course here. Before diving into the data science projects, one must know what data science is.
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