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From Coursera to Omdena in 1 year


Throughout the rest of my high school, I learned about game development, advanced data structures and algorithms, but not much about AI. The only exposure I had to Machine Learning was this website here, which didn't make a whole lot of sense to me back then. Fast forward, I returned to India and was attending Eastern Public School, finishing up my 12th grade with an International Baccalaureate diploma. I started the Stanford University Machine Learning course taught by Dr. Andrew Ng, The best part is it does not use any high level libraries to teach the concepts to you, so you have to use MATLAB to answer all the programming assignments.

TensorFlow 2.0 Practical


Online Courses Udemy - TensorFlow 2.0 Practical, Master Tensorflow 2.0, Google's most powerful Machine Learning Library, with 10 practical projects 4.3 (197 ratings), Created by Dr. Ryan Ahmed, Ph.D., MBA, Kirill Eremenko, Hadelin de Ponteves, SuperDataScience Team, Mitchell Bouchard, English [Auto-generated] Preview this Udemy course -. GET COUPON CODE Description Artificial Intelligence (AI) revolution is here and TensorFlow 2.0 is finally here to make it happen much faster! TensorFlow 2.0 is Google's most powerful, recently released open source platform to build and deploy AI models in practice. AI technology is experiencing exponential growth and is being widely adopted in the Healthcare, defense, banking, gaming, transportation and robotics industries. The purpose of this course is to provide students with practical knowledge of building, training, testing and deploying Artificial Neural Networks and Deep Learning models using TensorFlow 2.0 and Google Colab.

Artificial Intelligence in Digital Marketing Certification


This game-changing course in 2020 will cover artificial intelligence tools in content creation, curation, augmented reality and digital marketing and will take you on a glimpse into the future. We will also look at influencer marketing tools, content trends and a bit of competitor analysis through the use of BuzzSumo. Why learn this amazing artificial intelligence course and how is this a differentiator for content creators? This course can change your life if you are a content expert. Because, I will provide you with hands-on experience on creating tons and tons of articles for your blog for inbound marketing using an Artificial Intelligence content tool and you don't even have to write the content yourself - ever again.

Artificial Intelligence (AI) in the Classroom


AI is finally here and most of us are already actively using it in our day-to-day life. To prepare our future generation to harness these technologies, educators need to understand how they can use AI, use it to facilitate learning and solve real-world problems. The course is aimed at all educators who would like to use AI, irrespective of the topic which they teach. The course assumes no prior knowledge of AI and will start by introducing the basic concepts. It will then illustrate a number of fun exercises which can be used with the students, to help them understand these concepts.

Feature Engineering for Machine Learning


Online Courses Udemy | Feature Engineering for Machine Learning, Transform the variables in your data and build better performing machine learning models Created by Soledad Galli English [Auto] Preview this course GET COUPON CODE 100% Off Udemy Coupon . Free Udemy Courses . Online Classes

A Complete Guide on TensorFlow 2.0 using Keras API


Online Courses Udemy - A Complete Guide on TensorFlow 2.0 using Keras API, Build Amazing Applications of Deep Learning and Artificial Intelligence in TensorFlow 2.0 Created by Hadelin de Ponteves, Kirill Eremenko, SuperDataScience Team, Luka Anicin English [Auto] Students also bought Machine Learning A-Z: Hands-On Python & R In Data Science Data Analysis & Visualization Bootcamp - 2020 BESTSELLER R Programming A-Z: R For Data Science With Real Exercises! Practical Machine Learning by Example in Python Python for Statistical Analysis Preview this course GET COUPON CODE Description Welcome to Tensorflow 2.0! TensorFlow 2.0 has just been released, and it introduced many features that simplify the model development and maintenance processes. From the educational side, it boosts people's understanding by simplifying many complex concepts. From the industry point of view, models are much easier to understand, maintain, and develop.

Unsupervised Deep Learning in Python


Online Courses Udemy Unsupervised Deep Learning in Python, Theano / Tensorflow: Autoencoders, Restricted Boltzmann Machines, Deep Neural Networks, t-SNE and PCA Created by Lazy Programmer Inc. Students also bought Advanced AI: Deep Reinforcement Learning in Python Deep Learning: Recurrent Neural Networks in Python Ensemble Machine Learning in Python: Random Forest, AdaBoost Deep Learning: GANs and Variational Autoencoders Deep Learning Prerequisites: Linear Regression in Python Machine Learning and AI: Support Vector Machines in Python Preview this course GET COUPON CODE Description This course is the next logical step in my deep learning, data science, and machine learning series. I've done a lot of courses about deep learning, and I just released a course about unsupervised learning, where I talked about clustering and density estimation. So what do you get when you put these 2 together? In these course we'll start with some very basic stuff - principal components analysis (PCA), and a popular nonlinear dimensionality reduction technique known as t-SNE (t-distributed stochastic neighbor embedding). Next, we'll look at a special type of unsupervised neural network called the autoencoder.

Lecture Notes on Introduction to Machine Learning on Azure at @Udacity


The categorical data is converted in to the numerical format using ordinal encoding(ranking of categories from 0 to n-1, n is number of category) or one hot encoding(each category is column and its binary representation yes/no) to be used in machine learning models.

Natural Language Processing with Sequence Models


In Course 3 of the Natural Language Processing Specialization, offered by, Please make sure that you've completed Course 2 and are familiar with the basics of TensorFlow. If you'd like to prepare additionally, you can take Course 1: Neural Networks and Deep Learning of the Deep Learning Specialization. By the end of this Specialization, you will have designed NLP applications that perform question-answering and sentiment analysis, created tools to translate languages and summarize text, and even built a chatbot! This Specialization is designed and taught by two experts in NLP, machine learning, and deep learning.