Instructional Material
Convert Scanned Documents to Text. JPG to Excel
Convert image to editable excel. "Level Up" for Beginners who are interested in Big Data and Machine Learning (using Python). This Step-by-Step Course is intended to be an initiation to learn #BigData and #MachineLearning with #Python programming for absolute beginners that have no background in programming. In this course, we will step by step, using the example of real data, we will go through the main processes related to the topic "Big data and machine learning". Since the material turned out to be voluminous, I divided the course into five parts.
Machine Learning in Construction. Price and Time Prediction
This course is intended to be an initiation to learn #BigData and #MachineLearning & #AI with #Python programming for absolute beginners that have no background in programming. In this course, we will step by step, using the example of real data, we will go through the main processes related to the topic "Big data and machine learning". Since the material turned out to be voluminous, I divided the course into five parts. We will examine in detail the basic types, terms and algorithms of machine learning. We go through the basic concepts of machine learning that beginners need.
Predicting the age of abalone from physical measurements Part 1 - Projects Based Learning
Abalone is a common name for any of a group of small to very large sea snails, marine gastropod molluscs in the family Haliotidae. Other common names are ear shells, sea ears, and muttonfish or muttonshells in Australia, ormer in the UK, perlemoen in South Africa, and paua in New Zealand. The age of abalone is determined by cutting the shell through the cone, staining it, and counting the number of rings through a microscope a boring and time consuming task. Other measurements, which are easier to obtain, are used to predict the age. Given is the attribute name, attribute type, the measurement unit and a brief description.
Deep Learning with Keras and Tensorflow in R
Python was slowly becoming the de-facto language for Deep Learning models. In this course you will learn how to build powerful convolutional neural networks in R, from scratch. This special kind of deep networks is used to make accurate predictions in various fields of research, either academic or practical. If you want to use R for advanced tasks like image recognition, face detection or handwriting recognition, this course is the best place to start. All the procedures are explained live, step by step, in every detail. Most important, you will be able to apply immediately what you will learn, by simply replicating and adapting the code we will be using in the course.
Applied Machine Learning in R
They are powerful data mining techniques that allow you to detect patterns in your data or variables. For each technique, a number of practical exercises are proposed. By doing these exercises you'll actually apply in practice what you have learned. This course is your opportunity to become a machine learning expert in a few weeks only! With my video lectures, you will find it very easy to master the major machine learning techniques. Everything is shown live, step by step, so you can replicate any procedure at any time you need it. So click the "Enroll" button to get instant access to your machine learning course. It will surely provide you with new priceless skills. And, who knows, it could give you a tremendous career boost in the near future.
GIS for Drone Pilots using QGIS (w/ Airspace Data Template)
Prepare your drone flight, analyze the resulting data, and prepare professional reports using QGIS. GIS and Drone Technologies are both powerful tools for assisting people in analyzing the world we inhabit. Whether you are someone with GIS skills looking to add drones to your toolbelt, or a drone pilot who wants to level up their deliverable products, you are in the right place. Both these skills require very similar mindsets, such as an attention to detail, focus and accuracy. If you can do one, you can do the other, so why not do both!
Complete guide to begin with Python for Data Science
A complete guide to begin your python learning for data science, data analysis and machine learning. For those, who has never written a single code in entire life and want to move into data science or advanced python, this course provides you a simple approach to learn coding from scratch using python as a tool and master it with illustrations and assignments. For those, who are already experienced in coding, but want to move into advanced python, this course provides you ample hands-on exercises and assignments for deeply understanding the concept. In this course, you will be learning from the very basics - which includes basic numbers, arithmetic operations, lists, sets, tuples, dictionaries, loops, if else statements, nested dictionaries, functions, recursive functions etc. We will be using Jupyter notebook in order to execute all the codes.
TensorFlow 2.0: A Complete Guide on the Brand New TensorFlow
Udemy Coupon - TensorFlow 2.0: A Complete Guide on the Brand New TensorFlow Build Amazing Applications of Deep Learning and Artificial Intelligence in TensorFlow 2.0 4.2 (639 ratings) Created by Hadelin de Ponteves, Kirill Eremenko, SuperDataScience Team, Luka Anicin ย English [Auto-generated] Preview this Course - GET COUPON CODE
Top 3 Free Resources to Learn Linear Algebra for Machine Learning - KDnuggets
Mathematics is the core of all machine learning algorithms. And while it isn't a prerequisite to have formal math education in order to become a data scientist, you need to understand the principles of the subject well enough to successfully build models that add value. In an article I wrote previously, I explained the three branches of mathematics that were essential to gain a deeper understanding of ML algorithms -- statistics, calculus, and linear algebra. This article will solely focus on linear algebra, as it forms the backbone of machine learning model implementation. Linear algebra concepts like vectorization allow for faster computation speeds, and are implemented in libraries like Pandas, Scipy, and Scikit-Learn.
What's Trending in MLOps in 2022?
A model that never makes it into production is one that is incapable of producing value for a business or organization. Unfortunately, the percentage of models that make it out of development is still low. However, the field of MLOps is focused on this very problem and has come up with a number of solutions, best practices, and tools to help organizations effectively integrate machine learning and AI models into their business practices. These MLOps trends will be helpful beyond just 2022. To help you learn the tools and skills you need to implement MLOps in your organization, ODSC East 2022 will feature talks, workshops, and training sessions led by some of the best and brightest minds in the field.