In Part-1 we have covered how to get started with Machine Learning at beginner level. Here in Part-2 we learn machine learning at two other levels. Machine Learning and Artificial Intelligence are the two most trending technology everyone want to get learn and get started their career in these field. This field is not only in demand but also the highest paid profile. Here if you are at advanced level to learn machine learning and artificial intelligence follow these videos as you can gain more insights to start your career.
Machine Learning At Advanced Level
1. Machine Learning Recipes:
Machine learning is making systems so smart that they are getting closer & closer to replacing humans. In this these 10 min videos you will about the various applications of machine learning. By watching the first video itself you will be able to write your first code. In these videos you will learn about decision tree visualization, scikit- learn, tensorflow, how to build your own classifier, what is the most accurate features for your model and many more interesting concepts. The language used is Python. The videos are very informative and a must watch for any intermediate in data science.
2. Machine Learning with Text in Scikit-Learn:
Although numeric data is easy to work with in Python, most knowledge created by humans is actually raw, unstructured text. By learning how to transform text into data that is usable by machine learning models, you drastically increase the amount of data that your models can learn from. In this tutorial, you will learn to build and evaluate predictive models from real-world text using scikit-learn. By the end of this tutorial, you will be able to confidently build predictive models from text-based data along with feature extraction, model building and model evaluation. This tutorial was delivered in PyCon 2016.
3. Machine Learning for Hackers:
Ever wondered how Netflix recommends shows based on your choice or how Amazon recommends you products they think you might also like. For any machine learning practitioner, these questions are no brainer. In this tutorial, the speaker introduces you to machine learning and how it is being used to solve various problems, build AI based games and many other application of ML. Well not just an introduction to these applications but you will learn how to build movie recommender system, chatbots, AI game and AI reader & writer. There are 5 min videos with key takeaways. These videos are meant for any machine learning hacker and requires one to have thorough understanding of machine learning concepts.
4. Introduction to Machine Learning on Apache Spark MLlib:
Spark MLlib is a library for performing machine learning and associated tasks on massive data sets. With MLlib, fitting a machine learning model to a billion observations can take only a few lines of code. Along with this one can leverage hundreds of machines. In this tutorial, a senior data scientist from Cloudera introduces you through Apache Spark from scratch. You will learn about how Spark works and its execution model. The speaker has used several examples to explain the interactivity which Spark offers. It also covers the use of Spark's Data Frames API for fast data manipulation, as well as ML Pipelines for making the model development and refinement process easier.
5. Time Series Analysis with Python Intermediate:
In this tutorial, you will learn why should you use time series and what is the importance of time series analysis. The speaker provides a quick 10 mins introduction to Pandas to provide a refresher. Then you will see time series in action and learn how to deal with calendar dates in Pandas. The speaker will teach you how to understand the different time-stamped data like US-GIS, NIH, FRB, etc. Learn about the common time series analytical tools, prediction and classification in time series.
Applications of Machine Learning
1. Breakthroughs in Machine Learning:
Machine Learning is producing smarter gadgets and machines. Siri and Cortona is a result of major advances in machine learning. But, what goes behind creating these products. Let's learn that in this video from Google data science team. The team first takes you through speech recognition and how it has been made possible. Then understand how machine learning is used on graphs to make image classification and smart replies a reality. It is an interesting video which reveals all the backend operations a machine performs for three major machine learning applications developed by Google.
2. Machine Learning & Art:
The recent progress of machine learning is impressive, and the applications seem endless. Neural networks are incredible tools allowing artist not just to analyze but also manipulate and generate images, movies and music. In this video, the speaker explains how The Google Cultural institute in finding ways to use machine learning for art and culture. In my last article on deep learning videos, we saw a video to create neural art. In this video, the speakers take you through all the fun stuff one can do with machine learning like Train Mario games, create artful collages using machine learning, create digital interactive images & videos. It is a very interesting video and I would recommend everyone to must watch it. 3. Machine learning to decode the genome:
Machine Learning can also be applied for understanding human genome, revealing a whole new world of personalized medication. In this video, Anshul Kundaje assistant professor of genetics and of computer science at Stanford explains how machine learning can be used for this purpose. He explains how the genomes of healthy individuals can be compared with their family members diagonsed with a particular disease to identify disease associated genetic variants. I think this can be a revolutionary step in detecting early chances of diseases like Alzheimers and Cancer.
4. How computers are learning to be creative:
Here is one of the amazing videos I have come across on applications of machine learning. Deep Learning is a sub-field of artificial intelligence. Through deep learning, the aim of data scientists is to interpret the same functionality of a human brain into machines. In this Ted talk by Blaise Aguera Arcas, Principal Scientist at Google he shares how machine learning algorithms and neural nets are used to build machine perception. In this video he shows how neural nets trained to recognize images can be run in reverse, to generate the same images. He explains this with several visual examples.
5. How GrabTaxi uses machine learning to predict taxi availability:
Personally, to me it is surprising to see how machine learning can solve business problems at different levels. One such example is how Grab Taxi uses machine learning to tackle the problem of taxi availability. To handle this problem, Grab started a unique initiative of bidding for a ride by the drivers and the fastest bidder wins and is assigned the ride. Watch the full video to find out how they used machine learning to build a predictive model on drivers bidding probability and used real time data to solve the problem.
6. Getting Started with Amazon Machine Learning:
Amazon Machine Learning (Amazon ML) is a service that makes it easy for developers of all skill levels to use machine learning technology. Amazon Machine Learning's powerful algorithms create machine learning models by finding patterns in your existing data. In this tutorial, you will learn how to use machine learning with the data you already have to arrive at accurate and actionable predictions, i.e, to create smart applications. You will learn how to use and integrate Amazon ML into your applications to take advantage of predictive analysis in the cloud.
7. Amazon Go-world's most advanced shopping technology:
I think this is one of the most fascinating technologies that will blow off every hot & shot organized retail. Amazon is using computer vision, machine learning, deep learning algorithms and sensor fusions to give you an out of the world shopping experience. Just to be clear, I am not promoting Amazon Go but trying to show you what all machine learning can do.
8. 10 Machine Learning based Products You Must See:
To see what magic of machine learning can create, watch this video featuring robotics trained with artificial intelligence & computer vision. These devices behave like any other human. Meet these super smart robots who can perform any task you thought a machine won't be able to perform. This video is a revelation of how robotics may replace human beings in the few years.
9. Knowledge Graphs for a Connected World:
The Connected graph is the answer to optimal business strategies and the key for growth in today's world. The ability to utilize the connected data to understand the relationship between any user or customer. In this video, the speaker explains the graph database technology which uses AI, machine learning, and deep learning. You will learn about the basics of connected graphs and how they work. How AI forms the basis of these connected graphs and see knowledgeable connected graphs in action with popular use cases.
10. The AI Gaming Revolution:
Artificial intelligence powered computers have come a long way. The machines are so smart today that they can beat humans in any new game. Alpha Go gained significant attention when it won against the professional human Go player.
But the questions is what goes in their brain and how are they able to perform that well. In this video, you will learn about Heuristics, production systems and deep neural networks which has made AI games a reality.