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Introduction to Machine learning with Python
- 1. Machine Learning With Python Chariza Pladin Data Analyst - Accenture Inc. chariza.b.pladin@accenture.com AUG 2017
- 2. AGENDA ● Artificial Intelligence ● Machine Learning ● Introduction to Python ● Machine Learning Algorithms ● Supervised Learning ● Unsupervised Learning ● Q/A MACHINE LEARNING WITH PYTHON | AUG 2017
- 4. “Intelligence exhibited by machines, rather than humans or other animals” MACHINE LEARNING WITH PYTHON | AUG 2017
- 5. 1943 1950 1956 1968 1969 1973 1981 1990 1997 AI KEYNOTES THROUGHOUT TIME 2002 2005 2008 2010 2011 2014 WW2 Robot Story Top-Down Approach 2001: A Space Odyssey Shakey the Robot The AI Winter A solution for big business Back to Bottom-up Man vs machine Roomba War Machines Google’s Speech Recognition Dance Bots Man vs machine 21st century Are machine intelligent now?
- 7. “Gives computers the ability to learn without being explicitly programmed.” MACHINE LEARNING WITH PYTHON | AUG 2017
- 8. MACHINE LEARNING WITH PYTHON | AUG 2017
- 15. def checkColor(img): #lots of code def checkSize(img): #lots of code def checkTexture(img): #lots of code def analyzeShape(img): #lots of code MACHINE LEARNING WITH PYTHON | AUG 2017
- 16. ● Develop systems that can automatically adapt and customize themselves to individual users. ● Discover new knowledge from large databases (data mining) ● Ability to mimic human and replace certain monotonous tasks which require some intelligence. ● Develop systems that are too difficult/expensive to construct manually because they require specific and detailed skills or knowledge tuned to a specific task. MACHINE LEARNING WITH PYTHON | AUG 2017
- 21. ● Supervised Learning ● Unsupervised Learning ● Reinforcement Learning MACHINE LEARNING WITH PYTHON | AUG 2017
- 22. consist of a target / outcome variable (or dependent variable) which is to be predicted from a given set of predictors (independent variables). Using these set of variables, we generate a function that map inputs to desired outputs. The training process continues until the model achieves a desired level of accuracy on the training data. SUPERVISED LEARNING MACHINE LEARNING WITH PYTHON | AUG 2017
- 23. Create a classifier by finding patterns in examples. SUPERVISED LEARNING MACHINE LEARNING WITH PYTHON | AUG 2017 TRAIN CLASSIFIER MAKE PREDICTION COLLECT TRAINING DATA
- 24. SUPERVISED LEARNING MACHINE LEARNING WITH PYTHON | AUG 2017
- 25. do not have any target or outcome variable to predict / estimate. It is used for clustering population in different groups, which is widely used for segmenting customers in different groups for specific intervention. UNSUPERVISED LEARNING MACHINE LEARNING WITH PYTHON | AUG 2017
- 26. MACHINE LEARNING WITH PYTHON | AUG 2017
- 27. MACHINE LEARNING WITH PYTHON | AUG 2017
- 28. MACHINE LEARNING WITH PYTHON | AUG 2017 MACHINE LEARNING Q&A
- 29. MACHINE LEARNING WITH PYTHON | AUG 2017 THANK YOU ! :)