"One doesn't need to be a software engineer or a master coder. One just needs to be functional to get the job done. Most of the "hardwork" in any model is done by a function pulled from some pre-developed library, in any case. …"
L.V.'s Discussions
Question about connected cars
Started this discussion. Last reply by Page Schorer May 19, 2016. 1 Reply 0 Likes
With automated cars communicating with each other (machine-to-machine communications - thus the word connected cars), could we envision the following futurist scenario:Cars exchange their…Continue
Book: Deep Learning With Python
Started this discussion. Last reply by Patrick J. Hagan Jun 30, 2016. 1 Reply 4 Likes
From First Model, To State-of-the-Art ResultsDeep learning is the most interesting and powerful machine learning technique right now.Top deep learning libraries are available on the Python ecosystem…Continue
Kaggle Releases Data Sets About Global Warming: Make your own Predictions
Started Apr 13, 2016 0 Replies 0 Likes
Analyze the data, make your own conclusions about global warming and climate change (especially predictions), and post your results in the comment section below: this article will be featured and…Continue
Book: Mastering Python for Data Science
Started this discussion. Last reply by Patrick J. Hagan Jun 30, 2016. 1 Reply 5 Likes
About This BookMaster data science methods using Python and its librariesCreate data visualizations and mine for patternsAdvanced techniques for the four fundamentals of Data Science with Python -…Continue
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Vikrant Choudhary replied to L.V.'s discussion Java versus Python"I feel this is not the way it can be compared.. I know both and found effective in their respective fields."
Julia Kravchenko replied to L.V.'s discussion What pays most: R, Python, or SQL?"As for 2018, we've got the following figures in our salary report:Python developer in the USA gets around $160,000 (senior position) while junior specialists earn $87,000.
If we talk about UK, annual salaries will be: junior…"
Frederick T Williams liked L.V.'s blog post Deep Learning Networks: Advantages of ReLU over Sigmoid Function
L.V. posted a blog postDeep Learning Networks: Advantages of ReLU over Sigmoid Function
This was posted as a question on StackExchange. The state of the art of non-linearity is to use rectified linear units (ReLU) instead of sigmoid function in deep neural network. What are the advantages? I know that training a network when ReLU is used would be faster, and it is more biological inspired, what are the other advantages? (That is, any disadvantages of using sigmoid)?…See More
L.V.'s blog post was featuredDeep Learning Networks: Advantages of ReLU over Sigmoid Function
This was posted as a question on StackExchange. The state of the art of non-linearity is to use rectified linear units (ReLU) instead of sigmoid function in deep neural network. What are the advantages? I know that training a network when ReLU is used would be faster, and it is more biological inspired, what are the other advantages? (That is, any disadvantages of using sigmoid)?…See More
Mankovskaya replied to L.V.'s discussion What pays most: R, Python, or SQL?"The salaries definitely depend on the state you live in and additional skills you possess. Quick example, while living in San Francisco Python developers can earn approx $137,389 per year, but in New York it will be $130,517. …"
Frederick T Williams liked L.V.'s blog post New Book: Data Science: Mindset, Methodologies, and MisconceptionsJon Reade replied to L.V.'s discussion What pays most: R, Python, or SQL?"Agree completely with William on this. It's the same in the UK, small companies will pay way less than large ones, and you're more likely to need to be a jack of all trades. Newcastle might pay a £25k salary for the same job that…"
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L.V.'s Blog
Deep Learning Networks: Advantages of ReLU over Sigmoid Function
Posted on October 11, 2018 at 6:00pm 0 Comments 1 Like
This was posted as a question on StackExchange. The state of the art of non-linearity is to use rectified linear units (ReLU) instead of sigmoid function in deep neural network. What are the advantages? I know that training a network when ReLU is used would be faster, and it is more biological inspired, what are the other advantages? (That is, any disadvantages of using sigmoid)?…
Continue Deep Learning: AlphaGo Zero Explained In One Picture
Posted on January 4, 2018 at 6:00pm 1 Comment 7 Likes
Recently Google DeepMind announced AlphaGo Zero — an extraordinary achievement that has shown how it is possible to train an agent to a superhuman level in the highly complex and challenging domain of Go, ‘tabula rasa’ — that is, from a blank slate, with no human expert play used as training data.
It thrashed the previous reincarnation 100–0, using only 4TPUs instead of 48TPUs and a single…
Continue Choosing the Correct Type of Regression Analysis
Posted on January 4, 2018 at 6:00pm 0 Comments 4 Likes
Book: Machine Learning: a Probabilistic Perspective
Posted on November 15, 2017 at 6:00pm 1 Comment 4 Likes
Today’s Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach.
The coverage combines breadth and depth, offering necessary…
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