Which programming language should I master in order to get a job in machine learning or data science? This is a silver bullet problem. Many forums are debating this issue. I will provide my own answer in this article and explain why, but we have to look at some data first. After all, practitioners of machine learning and data science should keep this in mind: there is no right to speak without an investigation. Now let's look at some data. We use the trend search provided by the indeed.com website to extract statistics. These data are the frequency of searches for job-specific changes over time from job postings, indicating who the employer is looking for. But please note that this is not a civil survey that is most useful for which skills, but rather a trend that shows how the popularity of job skills evolves (more precisely, it may be close to the first derivative of job skill prevalence, since The results are the skills listed in the recruitment information plus the employment retraining skills minus the retirement and separation skills.) Ok, let's look at the data. I searched for skills combined with "machine learning" and "data science," with the most prominent programming languages ​​being Java, C, C++, and JavaScript. I also added the popular languages ​​Python and R for machine learning and data science like Scala to Spark - and Julia, considered the next generation of popular languages. After the query, we get the results as shown below. When we only focus on machine learning, we get similar data as shown below. First of all, we can see from the chart that it is difficult to adjust. In this case, many languages ​​are quite popular. Second, the popularity of all these languages ​​is skyrocketing, indicating that interest in machine learning and data science has increased over the past few years. Third, Python is clearly ahead, followed by Java, R, C++. Python goes beyond Java and gradually widens the gap, while the gap between Java and R is diminishing. I must admit that I was surprised to see that Java is in second place. I thought R was the second. Fourth, the growth of Scala is impressive. Almost no one used Scala three years ago, but now he can compete with other mature languages. This is especially true when we switch from trend graph to actual data view on indeed.com. Fifth, Julia's popularity is relatively poor, but it has certainly increased in recent months. Will Julia become one of the popular languages ​​for machine learning and data science? It is up to time to answer. If we hide Scala and Julia to magnify the views of other languages, it is certain that Python and R are growing faster than other languages. From this curve, perhaps the popularity of R will soon exceed Java. When we switch to "deep learning" to query, the data obtained is very different. In this query, Python is still ahead, but in turn it is C++, Java, C. R is only ranked fifth. It is clearly emphasized here that these are high performance computing languages. As a general machine learning language, Java will soon occupy the second position, and the R language will not reach the top in a short time. To my surprise, as the main language of the deep learning framework Torch, Lua is not on the list, and Julia is also absent. The answer to the original question should be clear now? Python, Java, and R are the most popular languages ​​in machine learning and data science. If your focus is on deep learning rather than general machine learning, you should learn more about C++, and secondly C needs to be concerned and learned. However, keep in mind that this is just one way to look at the problem. If you want to find a job in academia, or just want to learn machine learning and data science in your spare time, you may get different answers. As for my personal answer, I answered it on the blog earlier this year. In addition to being able to support many mainstream machine learning frameworks, Python is a good fit for me, just because I have a background in computer science. I also like to develop new algorithms in C++, because I have programmed in C++ for most of my career. But this is just my personal situation. People with different professional backgrounds may feel that another language is better. Statisticians with limited programming skills will prefer R. A strong Java developer can continue to use his favorite Java because Java has a large number of open source Java APIs. In the same way, so is the other languages. Therefore, my advice is to read other blogs that discuss the same issue and then invest a lot of time to learn a language.
ZGAR MINI
ZGAR electronic cigarette uses high-tech R&D, food grade disposable pod device and high-quality raw material. All package designs are Original IP. Our designer team is from Hong Kong. We have very high requirements for product quality, flavors taste and packaging design. The E-liquid is imported, materials are food grade, and assembly plant is medical-grade dust-free workshops.
From production to packaging, the whole system of tracking, efficient and orderly process, achieving daily efficient output. We pay attention to the details of each process control. The first class dust-free production workshop has passed the GMP food and drug production standard certification, ensuring quality and safety. We choose the products with a traceability system, which can not only effectively track and trace all kinds of data, but also ensure good product quality.
We offer best price, high quality Vape Device, E-Cigarette Vape Pen, Disposable Device Vape,Vape Pen Atomizer, Electronic cigarette to all over the world.
Much Better Vaping Experience!
ZGAR Vape Pen,Disposable Device Vape Pen,UK ZGAR MINI Wholesale,ZGAR MINI Disposable E-Cigarette OEM Vape Pen,ODM/OEM electronic cigarette,ZGAR Mini Device ZGAR INTERNATIONAL(HK)CO., LIMITED , https://www.zgarvapor.com
