Machine Learning - Do Androids Dream of Electric Sheep?
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Machine Learning is in vogue. There are lots of different ways of implementing Machine Learning such as Decision Trees, Probability Theory and Neural Networks. Neural Networks are the most mystifying.
During this presentation, you will discover investigations into building your own neural network. You will begin exploring the requirements needed to build the Mathematical model. Solving the model, you will learn the Mathematical functions necessary to create a usable Clojure library and evaluate your neural network.
YOU MAY ALSO LIKE:
- Fast Track to Machine Learning with Louis Dorard (in London on 15th - 17th July 2019)
- Leonardo De Marchi's Deep Learning Fundamentals (in London on 22nd - 23rd October 2019)
- Infiniteconf 2019 - A one-day community celebration of Big Data, Machine Learning and AI (in London on 4th July 2019)
- FullStack London 2019 - The Conference on JavaScript, Node & Internet of Things (in London on 10th - 12th July 2019)
- London TensorFlow.js (in London on 20th June 2019)
- Keynote by Dick Wall on Why API Design Matters, and Why Yours Sucks! (and mine sucks too!) (in London on 24th June 2019)
- Accessing Snap ML (SkillsCast recorded in June 2019)
- Snap Machine Learning (SkillsCast recorded in June 2019)
Thanks to our sponsors
Machine Learning - Do Androids Dream of Electric Sheep?
Rickesh Bedia
Rickesh is a Mathematics Graduate from Warwick University. After Graduation, he was encouraged to learn Clojure and joined JUXT. This gave him a platform to perform Clojure and Machine Learning in a professional environment.
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SkillsCast
Please log in to watch this conference skillscast.
Machine Learning is in vogue. There are lots of different ways of implementing Machine Learning such as Decision Trees, Probability Theory and Neural Networks. Neural Networks are the most mystifying.
During this presentation, you will discover investigations into building your own neural network. You will begin exploring the requirements needed to build the Mathematical model. Solving the model, you will learn the Mathematical functions necessary to create a usable Clojure library and evaluate your neural network.
YOU MAY ALSO LIKE:
- Fast Track to Machine Learning with Louis Dorard (in London on 15th - 17th July 2019)
- Leonardo De Marchi's Deep Learning Fundamentals (in London on 22nd - 23rd October 2019)
- Infiniteconf 2019 - A one-day community celebration of Big Data, Machine Learning and AI (in London on 4th July 2019)
- FullStack London 2019 - The Conference on JavaScript, Node & Internet of Things (in London on 10th - 12th July 2019)
- London TensorFlow.js (in London on 20th June 2019)
- Keynote by Dick Wall on Why API Design Matters, and Why Yours Sucks! (and mine sucks too!) (in London on 24th June 2019)
- Accessing Snap ML (SkillsCast recorded in June 2019)
- Snap Machine Learning (SkillsCast recorded in June 2019)
Thanks to our sponsors
-
About the Speaker
Machine Learning - Do Androids Dream of Electric Sheep?
Rickesh Bedia
Rickesh is a Mathematics Graduate from Warwick University. After Graduation, he was encouraged to learn Clojure and joined JUXT. This gave him a platform to perform Clojure and Machine Learning in a professional environment.