I'm a data science student, I'm doing an internship in company X. since I joined the company, no task was assigned directly to me. I was asking my tutor to give me a task so he told me to check the current model and see if I can make it better. I did that in ~2 weeks, I've read the idea behind the model, read his code, coded my approach and added the evaluation. When I finished doing it, I …
I currently work as a data scientist developing software that classifies PDF documents into certain categories, using Machine Learning models with Natural Language Processing methods. I am thinking about finding a certain niche or specialization to work in either full time or as a freelancer. I have some idea where Machine Learning (and Natural Language Processing) are being used in in actual businesses, for example Chatbots, Product Recommendation, etc., however i would like to know: What kind of Machine Learning …
I was reading Modern Optimization with R (Use R!) and wondering if a book like this exists in Python too? To be precise something that covers stochastic gradient descent and other advanced optimization techniques. Many thanks!
I am a college student, struggling to decide whether or not to take pure maths electives on topics such as real analysis and measure theory. If I were to take them then I would definitely have to invest a lot of time into them in order to understand them and get better grades. However I am considering the opportunity cost for this, as I could have learned new skills such as deepening my programming skills. How important was this to …
I have been trying to understand this for a long time, but this information proves to be incredibly elusive online. What are possible jobs that a pure Data Scientist, without much background knowledge, could be hired for in an Engineering team? I am aware, for instance, that supply chain can get some involvement. I don't mean the Business Intelligence positions, I want to get more involved with the engineering team, working on the products themselves (specially Aerospace or Railway). By …
I'm a freshman at a technology university and I want to be a Data Analyst. What major I should choose to learn: Computer Science or Science in Information Systems? And what skills do I need to equip to be a good Data Analyst? Group of topics: Artificial Intelligent, Domain-driven Data Mining, Predictive Analytics or the other: Software Project Management, Distributed Database, which one is more related to Data analysis? I'm quite puzzled and worried so I hope that professionals may …
Now that I have my engineering degree with a specialization in finance & quantitative analysis, I plan to start my career in Data Science Consulting. To develop my path a little, I took data science courses (some included in my engineering cursus, which I completed with others courses found on the internet), I carried out research on predictive problems during academic project and I did my end-of-studies internship as a data scientist. The community seems to be the most active …
I had a conversation with someone recently and mentioned my interest in data analysis and who I intended to learn the necessary skills and tools. They suggested to me that while it is great to learn the tools and build the skills there is little point in doing so unless i have specialized knowledge in a specific field. They basically summed it to that I'd just be like a builder with a pile of tools who could build a few …
I am data science enthusiast and have interest in NLP. How should I develop my understanding for the domain and prepare for the role of an NLP engineer? What are the must have skills to master NLP? Suggest few good reading resources/online courses
The title says it all, I want to transition from actuarial science to data science. My background: I have a BS and MS in pure mathematics, both with high GPA (3.94) and graduation with honors. My areas of study were highly theoretical (Algebraic Geometry), though I took some statistics courses, computer science, and economics as well. I am savvy with R, Python, Sql, etc. Unlike some pure-mathy types I do communicate well and I do well at translating business questions …
First of all this term sounds so obscure. Anyways..I am a software programmer. One of the languages I can code is Python. Speaking of Data I can use SQL and can do Data Scraping. What I figured out so far after reading soo many articles that Data Science is all about good at: 1- Stats 2- Algebra 3- Data Analysis 4- Visualisation. 5- Machine Learning. What I know so far: 1- Python Programming 2- Data scrapping in Python Can you …
Right now there is a lot of hype for data science. Everyone is learning it. There are lots of courses and boot camps being offered. Unlike software engineering, however, are data scientists required to have a specialization in a specific domain? For example, if you want to be a data scientist and like to work on topics in biology, would you need to know a lot about biology?
i want to become a data scientist. I studied applied statistics (actuarial science), so i have a great statistical background (regression, stochastic process, time series, just for mention a few). But now, I am going to do a master degree in Computer Science focus in Intelligent Systems. Here is my study plan: Machine learning Advanced machine learning Data mining Fuzzy logic Recommendation Systems Distributed Data Systems Cloud Computing Knowledge discovery Business Intelligence Information retrieval Text mining At the end, with …
I am a graduate student in Mathematics, and I have been recently offered a post-doc at a good university. While it is not a top school in the most strict sense of the word, it is one of the best positions in my field of research. However, I have recently started wondering whether academia is really the right choice for me, and I am considering learning data science with the intention of transitioning towards industry. The question is, assuming I …
Is advanced level SQL required to be competitive as a data scientist? Is it more important for a data analyst to be good in SQL? Is it enough to be able to extract data using simple SQL queries? I know it is faster to manipulate data in SQL than to copy data into R or Python, but are there any other advantages or disadvantages?
I have been trying to break into the bioinformatics space (and now, data science more generally). Although there are numerous challenges in this field and I am constantly learning to deal with them, I have have found the most consistent and intractible challenges are interpersonal, and they are unlike anything that my previous experience prepared me for. In particular, I find it very difficult to balance between getting the information I need (or think I need) to do a good …
I am close to completing my PhD in Nutritional Sciences. Pre-PhD I did research in developmental biology, tissue engineering and molecular biology in general. To say the least, my background is very broad. Since the beginning of my PhD program, I realized I wanted to pursue a career in data science. Throughout my PhD I have invested innumerable hours to acquire skills in programming and data analysis (understanding HPC environments, coding in R, Python, specific bioinformatic tools for my area …
I am a 35 year old IT professional who is purely technical. I am good at programming, learning new technologies, understanding them and implementing. I did not like mathematics at school, so I didn't score well in mathematics. I am very much interested in pursuing a career in Big Data analytics. I am more interested in Analytics rather than Big Data technologies (Hadoop etc.), though I do not dislike it. However, when I look around in the internet, I see …
I would consider myself a journeyman data scientist. Like most (I think), I made my first charts and did my first aggregations in high school and college, using Excel. As I went through college, grad school and ~7 years of work experience, I quickly picked up what I consider to be more advanced tools, like SQL, R, Python, Hadoop, LaTeX, etc. We are interviewing for a data scientist position and one candidate advertises himself as a "senior data scientist" (a …