This video will help you leverage the power of TensorFlow to perform advanced image processing. TensorFlow has been gaining immense popularity over the past few months, due to its power and simplicity to use. This video will help you leverage the power of TensorFlow to perform advanced image processing. This course is a continuation of the Intro to Computer Vision course, building on top of the skills learned in that course. In this course, you'll dive deeper as we cover more advanced computer vision concepts.

For building any product, whether it includes ML or not, the first step is to identify the problem you're trying to solve. ML is a great tool for solving some problems, but there are many where it's best to start simpler. In this post, let's consider working for a company building a hypothetical product for automatically transcribing university lectures. We're going to build an automatic speech recognition (ASR) system which is tuned to work well for lectures -- this is something that definitely needs machine learning at its core. The product team have decided to start small and focus initially on just Physics lectures as a proof of concept.

Latest update: Instead of SSD, I show you how to use RetinaNet, which is better and more modern. I show you both how to use a pretrained model and how to train one yourself with a custom dataset on Google Colab. This is one of the most exciting courses I've done and it really shows how fast and how far deep learning has come over the years. When I first started my deep learning series, I didn't ever consider that I'd make two courses on convolutional neural networks. I think what you'll find is that, this course is so entirely different from the previous one, you will be impressed at just how much material we have to cover.

NLP is literally the processing of textual data to gain insights from it. In this course you will build MULTIPLE practical systems using natural language processing, or NLP - the branch of machine learning and data science that deals with text and speech. This course is not part of my deep learning series, so it doesn't contain any hard math - just straight up coding in Python. All the materials for this course are FREE. After a brief discussion about what NLP is and what it can do, we will begin building very useful stuff.

The topics outlined below are taught using practical Python projects!

People who want to learn about machine learning and deep learning will work on five real-world projects. Are you ready to start your path to becoming a Data Scientist or ML Engineer? This comprehensive course will be your guide to learning how to use the power of Python to analyze data, create beautiful visualizations, and use powerful machine learning algorithms! Data Scientist has been ranked the number one job on Glassdoor and the average salary of a data scientist is over $120,000 in the United States according to Indeed! Data Science is a rewarding career that allows you to solve some of the world's most interesting problems!

Gain a competitive edge in the world of Computer Vision through this course by learning how to do Smart Data Extraction from Pdf and Images. Gain a competitive edge in the world of Computer Vision through this course by learning how to do Smart Data Extraction from Pdf and Images. The technology landscape of world has brought in cognitive skills at the forefront where major emphasis is on intelligent data extraction. This becomes more complex due to the huge variety of input documents such as pdf document with structured data, scanned pdf document and word document. This course aims to solve this challenging problem by helping you to understand these various formats and then empower you to do smart data extraction using Python, Pandas, OCR, Tesseract, PyTesseract, OpenCV, Spacy and NER concepts.

Understand how to overcome RPA Implementation Challenges · Have a good grasp on how to Prepare and Launch a RPA project · Identify how to select the right process ... Robotics Process Automation(RPA) is changing the way we work and has become an integral element for any company who is thinking about digital transformation. This market is growing at a rapid pace and professionals need to evolve to become a part of this intelligent digital workforce. Do you want to be in the smart crowd and take the RPA Path? Then, this course is for you as it aims to answer the Why, What and How of RPA Implementation by adopting a step-by-step approach. We will teach you the essentials of RPA, explain how to overcome RPA Challenges like Process Analysis, Process Identification, Building an RPA team for RPA Managers, Business Case Issues and ROI Analysis through use cases.

In this complete deep reinforcement learning course you will learn a repeatable framework for reading and implementing deep reinforcement learning research ... In this complete deep reinforcement learning course you will learn a repeatable framework for reading and implementing deep reinforcement learning research papers. You will read the original papers that introduced the Deep Q learning, Double Deep Q learning, and Dueling Deep Q learning algorithms. You will then learn how to implement these in pythonic and concise PyTorch code, that can be extended to include any future deep Q learning algorithms. These algorithms will be used to solve a variety of environments from the Open AI gym's Atari library, including Pong, Breakout, and Bankheist. You will learn the key to making these Deep Q Learning algorithms work, which is how to modify the Open AI Gym's Atari library to meet the specifications of the original Deep Q Learning papers.

I will recommend this class to any one looking towards Data Science" "This course so far is breaking down the content into smart bite-size pieces and the professor explains everything patiently and gives just enough background so that I do not feel lost." "This course is really good for me. it is easy to understand and it covers a wide range of NLP topics from the basics, machine learning to Deep Learning. The codes used is practical and useful. I definitely satisfy with the content and surely recommend to everyone who is interested in Natural Language Processing"