Adnan Masood, a Machine Learning Phd's musings on Life, Technology, Research & Development
Microsoft Machine Learning and Data Science Summit promised to connect Big Data engineers, Data Scientists, Machine Learning practitioners and managers to share best practices, to Dive deep & learn, and to facilitate Think big & execute fast ideas. In my experience, the summit met majority of its goals and it was a great start. Microsoft has graciously made majority…
Microsoft Machine Learning & Data Science Summit is taking place in conjunction with Microsoft Ignite at Georgia World Congress Center on September 26 – 27, 2016 in Atlanta where thought leaders and Microsoft engineers will discuss the latest Big Data, Machine Learning, Artificial Intelligence, and Open Source techniques and technologies. I am exited to attend the summit due…
“May the queries flow, and the pager stay silent. —Traditional SRE blessing” Like *.js, DevOps / SRE isn’t completely immune from the dilemma of choice, or confusion as a service as some would like to call. Should it be Nagios or Zabbix or Cacti or Zenoss or Borgmon? Regardless of which tool one decides for monitoring usage,…
Apache Spark is a general purpose cluster computing platform which extends map-reduce to support multiple computation types including but not limited to stream processing and interactive queries. Last week IBM's Moktar Kandil presented at the Tampa Hadoop and Tampa Data Science Group Joint meetup on the topic of exploring Apache Spark. Apache Spark for Azure HD-Insight Following are…
A friend recently asked about a good book on data science, with python. I have been trying to go through the current landscape of books for a course I am teaching this summer, so here is my recommendation. There are several other good ones out there, but this one quite fits the newbie bill. So…
Pedro Domingos' The Master Algorithm - How the Quest for the Ultimate Learning Machine Will Remake Our World is an interesting and thought provoking book about the state of machine learning, data science, and artificial intelligence. Categorizing, classifying and clearly representing the ideas around any rapidly developing/evolving field is hard job. Machine learning with its…
During a discussion yesterday with software architect extraordinaire David Lazar regarding how everything old is new again, the topic of deep neural networks and its amazing success was brought up. Unless one is living under a rock for past five years, the advancements in artificial neural networks (ANN) has been quite significant and noteworthy. Since the…
On the final day (day 5) the agenda for the MIT Machine learning course was as follows: Generative models, mixtures, EM algorithm Semi-supervised and active learning Tagging, information extraction The day started with Dr. Jakkola's discusion on parameter selection, generative learning algorithms, Learning Generative Models via Discriminative Approaches, and Generative and Discriminative Models. This led to the questions such…
So after having an awesome Day 1 @ MIT, I was in CSAIL library and met Pedro Ortega, NIPS 2015 Program Manager @adaptiveagents. Celebrity sighting! Today on Day 2, Dr. Jaakkola (Bio) (Personal Webpage) professor, Electrical Engineering and Computer Science/Computer Science and Artificial Intelligence Laboratory (CSAIL), went over the following . Non-linear classification and regression, kernels Passive aggressive algorithm Overfitting, regularization, generalization Content…