BigDataFr recommends: The Data Science Industry: Who Does What Excerpt Nowadays, the data science field is hot, and it is unlikely that this will change in the near future. While a data driven approach is finding its way into all facets of business, companies are fiercely fighting for the best data analytic skills that are […]
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[analyticsvidhya] BigDataFr recommends: Nobody Tells You – 5 things Big Data ‘CAN’ and ‘Cannot’ Do
BigDataFr recommends: Nobody Tells You – 5 things Big Data ‘CAN’ and ‘Cannot’ Do Excerpt “Big Data makes us smarter, not wiser.” – Tim Leberecht. The term ‘Big Data’ got introduced in 1940s. Companies around the world have put in ceaseless efforts to explore its potential. The global tech giants have massively increased their spending […]
[analyticsvidhya] BigDataFr recommends: Exclusive Interview with SRK, Sr. Data Scientist, Kaggle Rank 25 #datascientist
BigDataFr recommends: Exclusive Interview with SRK, Sr. Data Scientist, Kaggle Rank 25 Excerpt […] Mr. Sudalai Rajkumar a.k.a SRK, Sr. Data Scientist, Tiger Analytics has become a huge inspiration for aspiring data scientist around the world. I’ve seen lots of people, driven by the spark of becoming a data scientist, but tend to develop disinterest […]
[Dataconomy] BigDataFr recommends: Top 10 Big Data Videos on Youtube #machinelearning
BigDataFr recommends: Top 10 Big Data Videos on Youtube Whether you’re entirely new to the field of big data, or looking to expand your machine learning knowledge; whether you have 3 hours or 3 minutes; whether you want you want to know more about the technology, or the high-level applications- this list is a sample […]
[Kdnuggets] BigDataFr recommends: 60+ Free Books on Big Data #datascientist
BigDataFr recommends:
[Kdnuggets] BigDataFr recommends: 60+ Free Books on Big Data
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[arXiv] BigDataFr recommends: Preconditioned Data Sparsification for Big Data with Applications to PCA and K-means
BigDataFr recommends: Preconditioned Data Sparsification for Big Data with Applications to PCA and K-means Excerpt We analyze a compression scheme for large data sets that randomly keeps a small percentage of the components of each data sample. The benefit is that the output is a sparse matrix and therefore subsequent processing, such as PCA or […]
[analyticsvidhya] BigDataFr recommends: 13 Tips to make you awesome in Data Science / Analytics Jobs
BigDataFr recommends: 13 Tips to make you awesome in Data Science / Analytics Jobs Excerpt […] However, the miserable part was, less than 30% of the data science projects actually got implemented to their potential. I got shattered realizing that my efforts got wasted. But, I wasn’t the only one. Almost, every other analyst had […]
[O’R Video – #StrataHadoop] BigDataFr recommends: 10 Problems with Qualitative Data – Farrah Bostic Keynote
BigDataFr recommends: 10 Problems with Qualitative Data – Farrah Bostic Keynote
[O’R] BigDataFr recommends: Beyond algorithms: Optimizing the search experience
BigDataFr recommends: Beyond algorithms: Optimizing the search experience We live in a golden age of algorithms. Even though we’ve had search engines, speech recognition, and computer vision systems for decades, only in the last several years have they become good enough to move out of the lab and into tools we use everyday — products […]