Get yourself trained on Artificial Intelligence Bootcamp with this Online Training Artificial Intelligence Bootcamp 44 projects Ivy League pro.
Online Training Artificial Intelligence Bootcamp 44 projects Ivy League pro
My name is GP. Iused AI to classify brain tumors. Ihave 11 publications on pubmed talking about that. I went to Cornell University and taught at Cornell, Amherst and UCSF. I worked at UCSFand NIH.AI and Data Science are taking over the world! Well sort of, and not exactly yet. This is the perfect time to hone you skills in AI,data analysis, and robotics, Artificial Intelligence has taken the world by storm as a major field of research and development. Python has surfaced as the dominantlanguage in intelligence and machine learningprogramming because of its simplicity and flexibility, in addition to its great support for open source libraries and TensorFlow.This video course is built for those with a NO understanding of artificial intelligence or Calculus and linear Algebra. We will introduce youto advanced artificial intelligence projects and techniques that are valuable for engineering, biological research, chemical research, financial, business, social, analytic, marketing (KPI), and so many more industries. Knowing how to analyze data will optimize your time and your money. There is no field where having an understanding of AI will be a disadvantage. AI really is the future.We have many projects, such natural language processing , handwriting recognition, interpolation, compression, bayesian analysis, hyperplanes (and other linear algebra concepts). ALLTHECODEISINCLUDED ANDEASYTOEXECUTE. You can type along or just execute code in Jupyter if you are pressed for time and would like to have the satisfaction of having the course hold your hand.Iuse the AI I created in this course to trade stock. You can use AI to do whatever you want. These are the projects which we cover.For Data Science / Machine Learning / Artificial Intelligence1. Machine Learning2. Training Algorithm3. SciKit4. Data Preprocessing5. Dimesionality Reduction6. Hyperparemeter Optimization7. Ensemble Learning8. Sentiment Analysis 9. Regression Analysis10.Cluster Analysis11. Artificial Neural Networks12. TensorFlow13. TensorFlow Workshop14. Convolutional Neural Networks15. Recurrent Neural NetworksTraditional statistics and Machine Learning1. Descriptive Statistics2.Classical Inference Proportions3. Classical InferenceMeans4. Bayesian Analysis5. Bayesian Inference Proportions6. Bayesian Inference Means7. Correlations11. KNN12. Decision Tree13. Random Forests14. OLS15. Evaluating Linear Model16. Ridge Regression17. LASSO Regression18. Interpolation19. Perceptron Basic20. Training Neural Network21. Regression Neural Network22. Clustering23. Evaluating Cluster Model24. kMeans25. Hierarchal26. Spectral27. PCA28. SVD29. Low Dimensional
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As a society, we spend hundreds of billions of dollars measuring the return on our financial assets. Yet, at the same time, we still haven’t found convincing ways of measuring the return on our investments in developing people.
And I get it: If my bank account pays me 1% a year, I can measure it to the penny. We’ve been collectively trained to expect neat and precise ROI calculations on everything, so when it’s applied to something as seemingly squishy as how effectively people are learning in the workplace, the natural inclination is to throw up our hands and say it can’t be done. But we need to figure this out. In a world where skills beat capital, the winners and losers of the next 30 years will be determined by their ability to attract and develop great talent.
Fortunately, corporate learning & development (L&D), like most business functions, is evolving quickly. We can embrace some level of ambiguity and have rigor when measuring the ROI of learning. It just might look a little different than an M.B.A. would expect to see in an Excel model.