David Nishimoto
ML - The way the world works - analyzing how things work
Machine learning is the most important technological breakthrough in the 21st century. Listen to my views on the future of machine learning. Code demonstrations on YouTube under my channel David Nishimoto
Author
David Nishimoto
Category
Podcast website
Latest episode
Mar 26, 2024
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Episodes
Cog, Ghenhis, kismet and augment finite state machines 10.06.2020 21:59
Ritchie says to Kismet, “I want to show you this watch my girlfriend gave me.” Kismet dutifully looks at the watch. Kismet was picking up on the social clues and the directions of attention. When Ritchie brought the watch into Kismets center of view, a few inches below his face where Kismet was foveated and when he brought his index finger up and tapped the watch the motion actived Kismets attenti...
Kshitij Bichave introduces beginners to reinforced learning 09.06.2020 38:04
Learn how to get started in reinforced learning . Learn about the major breakthroughs in game playing and physics engines making reinforced learning interesting to use. Learn about reinforcement tools like open ai gym, or dota Rl coach, ray, rlkit, truffle
The shortage is not data, the shortage is logic on the edge 06.06.2020 45:20
Machines could create logic and language on the edge
Honest Business 03.06.2020 16:47
The complete idea: Several peopled involved in decision-making combined are not as powerful as a single vision. Accepting conventional solutions dilutes great ideas. Wo from covering up sin: "A completely honest and straight forward announcement to the public would have been more effective."
The feds bond buying reasons in the primary and secondary bond market and the affect on etfs 31.05.2020 31:03
The announcement of the creation of the smccf caused corporate bond ETFs to line up with their NAVs. I provide a more detailed debate on the feds actions
Junk bonds 30.05.2020 44:21
What could happen because of destabilization in the junk bond market
Mechanisms of the mind 29.05.2020 26:03
The brain may not be as difficult to understand as previously thought. Instead, the problem may be it is too easy to understand.
Ryan Russon talks about human in the loop adding value through automation 27.05.2020 28:34
We talk about learning from the past and making predictions in the future. It is more important to develop small developments that have fast return on investment than to build spocks brain https://www.meetup.com/Machine-Learning-Utah/ https://www.meetup.com/utah-data-engineering-meetup/ https://www.meetup.com/SLCPython/
Cnn networks and pooling and regularization and drop rate 27.05.2020 8:40
Visualizing your network to understand why it work
Business process improvement 25.05.2020 25:43
When an organization fails to make continuous simplification efforts a major portion of the managing process, it invites difficulty and poor performance; simplification is achieved by combining similar activities, reducing the amount of handling (reduce delays caused by handoffs and decision making), eliminating unused data and copies, and refining standard reporting.
Leading on the Competitive Edge 22.05.2020 7:43
Even in the worst employment environments a person has a 33% chance of improvement through creativity and an imaginative idea is needed.
Convolution neural networks and deep learning 21.05.2020 20:34
Cnn are the foundation of object recognition and a form of deep learning
Ai and ml recap for the week. Thoughts about the future 16.05.2020 43:45
Talking about this week
Deep learning with keras - linear and categorical classification 16.05.2020 21:24
Building different types of multi layer networks to find signal
Mechanisms of the mind: interest and importance and model building 15.05.2020 29:23
Once a model is constructed, it has a life and working of its own. With a model, you put the pieces together and learn from what happens. A model is a method of transferring some relationship or process from its actual setting to a setting where it is more conveniently studied. In a model, relationships and processes are preserved unchanged though the things that are being related may be changed....
Ideas that stick 14.05.2020 13:30
We must explain our ideas in terms of human actions, in terms of sensory information. Mission statements, synergies, strategies, visions - they are often ambiguous to the point of being meaningless.
Kimi Nishimoto talks about breathing behaviors affecting sleep and health 13.05.2020 30:23
http://www.mouthmusclememory.com. Nasal congestion: leads to: not enough airflow or oxygen to the brain and body. We will have to use the emergency system aka mouth breathe to get enough airflow. Nasal congestion can be caused by allergies, rhinitis (stuffy nasal passages), food intolerances, mouth breathing, environment, underdeveloped maxilla bone and a high palate and smaller nasal cavity. Tong...
Mind set, future consumer behavior is embedded in current trend 12.05.2020 13:14
The future is embedded in the present. The future being embedded in the present does not mean extrapolating everything into the future. It means finding seeds of the future in the ground and not in the wide sky. In other words, change will take time and don’t get to far from what the crowd thinks and is demanding as emerging trends, products and services.
How consumers think and how to find meaning from data 10.05.2020 20:48
Market analysis
Machine learning and analyzing risks for public utilities 09.05.2020 30:13
Risk is one area that ai can be applied
Kmeans clustering, hierarchical clustering and sentiment analysis to find trend 07.05.2020 10:58
Normalizing data to reduce variance is necessary preparation of data. Normalizing is rescaling they data to a standard deviation of 1. Sentiment analysis can analyze text content for negative or positive words.
K means clustering 05.05.2020 9:51
Unsupervised learning
Hidden order - understanding the reasons for reinforced learning 02.05.2020 32:32
Consider a many-player game played over and over. Each player keeps changing his strategy until no further change will make him better off. Equilibrium is reached when each player has chosen a strategy that is optimal for him, given the strategies that the other players are following.
How to build actionable machine learning decisions in production 30.04.2020 21:36
Everything starts with inference about a business situation . It then moves to observation and experimentation. An finally if an case for impact can be built into ml production either through automation or detection
Logistic regression vs support vector machine 28.04.2020 23:40
C controls the degree of regularization. Gamma controls the smoothness of the boundary. Kernel can improve speed. Penalty controls the loss function
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