2017 Sep Opinions, Interviewshttp likes 69
All (108) | Courses, Education (9) | Meetings (14) | News, Features (23) | Opinions, Interviews (22) | Tutorials, Overviews (33) | Webcasts & Webinars (7)
- How to win Kaggle competition based on NLP task, if you are not an NLP expert - Sep 29, 2017.
Here is how we got one of the best results in a Kaggle challenge remarkable for a number of interesting findings and controversies among the participants.
- Key Takeaways from AI Conference in San Francisco 2017 – Day 1 - Sep 29, 2017.
Highlights and key takeaways from day 1 of AI Conference San Francisco 2017, including current state review, future trends, and top recommendations for AI initiatives.
- AI Conference in San Francisco, Sep 2017 – highlights and key ideas - Sep 28, 2017.
Highlights from recent AI Conference include the inevitable merger of IQ and EQ in computing, Deep learning to fight cancer, AI as the new electricity and advice from Andrew Ng, Deep reinforcement learning advances and frontiers, and Tim O’Reilly analysis of concerns that AI is the single biggest threat to the survival of humanity.
- Machine Learning Reveals 9 Elements of Deal-Closing Sales - Sep 26, 2017.
The data science team at Gong.io analyzed over 67,000 sales calls/demos to understand the patterns that close deals. Here is what we found.
- 10 Things Everyone Should Know About Machine Learning - Sep 26, 2017.
The author often finds himself explaining machine learning to non-experts. These are 10 things that he believes everyone should know, which he offers as a public service announcement.
- How To Lie With Numbers - Sep 21, 2017.
It takes less effort to lie without numbers, but there are now more numbers and more ways to lie with them than ever before. Poor Reverend Bayes, who understood the true meaning of "evidence".
- How To Become a 10x Data Scientist, part 2 - Sep 19, 2017.
A 10x developer is someone who is 10 times more productive than average. We adapt tips and tricks from the developer community to help you become a more proficient data scientist loved by team members, including code design and selecting right tools for the job.
- How To Become a 10x Data Scientist, part 1 - Sep 18, 2017.
A 10x developer is someone who is 10 times more productive than average. We adapt tips and tricks from the developer community to help you become a more proficient data scientist loved by team members and stakeholders.
- Will AI kill us all after taking our jobs? - Sep 15, 2017.
We are now in the middle of an AI hype wave which will decline. This is why I think that AI will take 100 or more years to become sentient, only after completely different AI systems will be created.
- Data Science and the Imposter Syndrome - Sep 15, 2017.
You are not the only one who wonders how much longer they can get away with pretending to be a data scientist. You are not the only one who has nightmares about being laughed out of your next interview.
- How SnotBots, Surveys and NASA are saving our oceans - Sep 14, 2017.
There are many projects using computer vision systems, machine learning and large data sets to hopefully make a difference to our oceans and gain the knowledge to have a real impact on future sustainability.
- Python vs R – Who Is Really Ahead in Data Science, Machine Learning? - Sep 12, 2017.
We examine Google Trends, job trends, and more and note that while Python has only a small advantage among current Data Science and Machine Learning related jobs, this advantage is likely to increase in the future.
- Top 10 Machine Learning Use Cases: Part 2 - Sep 11, 2017.
This post is the second in a series whose aim is to shake up our intuitions about what machine learning is making possible in specific sectors — to look beyond the set of use cases that always come to mind.
- The new Enigma Public – the platform connecting people to data - Sep 11, 2017.
Public data has tremendous potential and different people can use it to solve variety of problems. Enigma relaunches Enigma Public — the platform connecting people to data.
- I built a chatbot in 2 hours and this is what I learned - Sep 7, 2017.
I set out to test two things: 1) building a bot is useless from a business perspective and 2) building bots is crazy tough. Here is what I learned.
- Decoding AI: Making the Case for Artificial Intelligence - Sep 7, 2017.
The question is no longer ‘can we get machines to do this or that’ (the answer is yes for most things you can think of), question now is ‘where all do we want to do it?’
- Big Data or Big BS? - Sep 7, 2017.
Data and analysis of data have, in some form, been used to aid decision making since ancient times. So why, after all these centuries are data and analytics not more embedded in corporate decision making?
- Are Data Lakes Fake News? - Sep 6, 2017.
The quick answer is yes, and the biggest problem is that the term “Data Lakes” has been overloaded by vendors and analysts with different meanings, resulting in an ill-defined and blurry concept.
- Putting the “Science” Back in Data Science - Sep 6, 2017.
The scientific method to approach a problem, in my point of view, is the best way to tackle a problem and offer the best solution. If you start your data analysis by simply stating hypotheses and applying Machine Learning algorithms, this is the wrong way.
- Closing the Insights-to-Action Gap - Sep 5, 2017.
There are many types of analytics for getting insight out of data, but the bigger and more difficult challenge is turning that insight into action. What should we do differently based on your findings?
- Data Science: (not) the preferred nomenclature - Sep 4, 2017.
The term Data Science should describe the “Science OF Data”, while doing Science WITH Data could be called “Data-Driven Science”. Whatever your preferred term, reinforcing the distinction will help establish the Science OF Data and doing Science WITH Data as bona-fide disciplines.
- Search Millions of Documents for Thousands of Keywords in a Flash - Sep 1, 2017.
We present a python library called FlashText that can search or replace keywords / synonyms in documents in O(n) – linear time.