This solution illustrates the power and utility of BigQuery and Cloud Datalab as tools for quantitative analysis. The solution provides an introduction (this document) and gets you set up to run a notebook-based Cloud Datalab tutorial. If you’re a quantitative analyst, you use a … Continue reading Analyzing Financial Time Series Using BigQuery and Cloud Datalab
Hi I am a student in XYZ school but don’t think me a kid I know pretty well Deep learning for starter I can tell you the difference between perceptron and Deep Neural Networks .I bet 40% of you even … Continue reading When Mom can’t figure it out whether there is a cat or dog Data Raconteur son build a classifier for her mom.
Computer vision is an interdisciplinary scientific field that deals with how computers can be made to gain high-level understanding from digital images or videos. From the perspective of engineering, it seeks to automate tasks that the human visual system can do. what computer vision consist of : Artificial intelligence: Areas of artificial intelligence deal with autonomous planning or deliberation for robotical systems to navigate through an environment. A detailed understanding of these environments is required to navigate through them. Information about the environment could be provided by a computer vision system, acting as a vision sensor and providing high-level information about the environment and the robot. Artificial intelligence … Continue reading What is Computer Vision An Introduction
Ceiling Analysis is a way to systematically find the weakest component of your system, and therefore optimising that weakest component would best serve your time to bring the greatest improvement to the overall system. Why it is important in case of deep learning? Ceiling analysis is the process of manually overriding each component in your system to provide 100% accurate predictions with that component. Thereafter, you can observe the overall improvement of your deep learning system component by component. For photo OCR example, this is what we might have: Component Accuracy Note Overall system 72% Text Detection (TD) 89% Make … Continue reading Ceiling Analysis in Machine Learning?
This post is inspired by Andrew Ng’s deep learning specialization so if you are really interested in this project do check the course. So here comes the questions why ML stratergy? well the answer can be pretty motivating suppose you … Continue reading ML Strategy for Machine Learning Projects
Before we Start our journey let’s explore what is spark and what is tensorflow and why we want them to be combined. Apache Spark™ is a unified analytics engine for large-scale data processing. Features: Speed: Run workloads 100x faster. Apache Spark achieves high performance for both batch and streaming data, using a state-of-the-art DAG scheduler, a query optimizer, and a physical execution engine.(DAG means ) Logistic regression in Hadoop and Spark Ease of Use: Write applications quickly in Java, Scala, Python, R, and SQL.Spark offers over 80 high-level operators that make it easy to build parallel apps. And you can use … Continue reading You Can Blend Apache Spark And Tensorflow To Build Potential Deep Learning Solutions
As you Explore the dataset in the past post in this post our key focus will be building sample model to test our machine learning knowledge and in the last post we will build it in scale and deploy .If You have not read my previous post(this will hurt me ) you can read it here before continue to this one or recap it if you forget the dataset and aim of our project(not life). First we need to create our dataset for our sample model because if you remembered we have millions of rows that we can’t fit in … Continue reading End To End Scalable Machine Learning Project On Google Cloud With Beautiful Front End with Big Data-I