Deep Learning with TensorFlow, Keras, and PyTorch Training

Colleagues, Deep Learning with TensorFlow, Keras, and PyTorch is an introduction to that brings the revolutionary machine-learning approach to life with interactive demos from the most popular deep learning library, TensorFlow, and its high-level API, Keras, as well as the hot new library PyTorch. Essential theory is whiteboarded to provide an intuitive understanding of deep learning’s underlying foundations; i.e., artificial neural networks. Paired with tips for overcoming common pitfalls and hands-on code run-throughs provided in Python-based Jupyter Notebooks, this foundational knowledge empowers individuals with no previous understanding of neural networks to build powerful state-of-the-art deep learning models. Learn how to: Build deep learning models in all the major libraries: TensorFlow, Keras, and PyTorch, Understand the language and theory of artificial neural networks, Excel in machine vision, natural language processing, and reinforcement learning, Create algorithms with state-of-the-art performance by fine-tuning model architectures, and Complete your own Deep Learning projects. Core skills you will gain include: 1) Deep Learning and Artificial Intelligence, 2) How Deep Learning Works, 3) High-Performance Deep Learning Networks, 4) Convolutional Neural Networks, and 5) Moving Forward with Your Own Deep Learning Projects (Capstone Project).

Register today at: https://tinyurl.com/yxxqzr9t

Career success awaits you, Lawrence Wilson – Artificial Intelligence Academy

Deep Learning with TensorFlow: Application Training of Deep Neural Networks to Machine Learning Tasks

Machine Learning colleagues, take your career and income to the next level. This training program includes over 6 hours of video instruction - Deep Learning with TensorFlow is an introduction to Deep Learning that bring the revolutionary machine-learning approach to life with interactive demos from the most popular Deep Learning library, TensorFlow, and its high-level API, Keras. Essential theory is whiteboarded to provide an intuitive understanding of Deep Learning’s underlying foundations, i.e., artificial neural networks. Paired with tips for overcoming common pitfalls and hands-on code run-throughs provided in Python-based Jupyter Notebooks. Keras is an open-source neural-network library written in Python.  The Jupyter Notebook is an interactive computing environment that enables users to author notebook documents. The five learning modules include: 1) Introduction to Deep Learning, 2) How Deep Learning Works, 3) Convolutional Networks, 4) Introduction to TensorFlow, and 5) Improving Deep Networks.

Register today at: https://tinyurl.com/qoy6pvt

Career success awaits you, Lawrence Wilson – Artificial Intelligence Academy

Deep Learning with TensorFlow, Keras, and PyTorch Training

Colleagues, Deep Learning with TensorFlow, Keras, and PyTorch LiveLessons is an introduction to that brings the revolutionary machine-learning approach to life with interactive demos from the most popular deep learning library, TensorFlow, and its high-level API, Keras, as well as the hot new library PyTorch. Essential theory is whiteboarded to provide an intuitive understanding of deep learning’s underlying foundations; i.e., artificial neural networks. Paired with tips for overcoming common pitfalls and hands-on code run-throughs provided in Python-based Jupyter Notebooks, this foundational knowledge empowers individuals with no previous understanding of neural networks to build powerful state-of-the-art deep learning models. Learn how to: Build deep learning models in all the major libraries: TensorFlow, Keras, and PyTorch, Understand the language and theory of artificial neural networks, Excel in machine vision, natural language processing, and reinforcement learning, Create algorithms with state-of-the-art performance by fine-tuning model architectures, and Complete your own Deep Learning projects. Core skills you will gain include: 1) Deep Learning and Artificial Intelligence, 2) How Deep Learning Works, 3) High-Performance Deep Learning Networks, 4) Convolutional Neural Networks, and 5) Moving Forward with Your Own Deep Learning Projects (Capstone Project).

Register today at: https://tinyurl.com/yxxqzr9t

Career success awaits you, Lawrence Wilson – Artificial Intelligence Academy

Discover the Top 5 Training Programs for 2020 to Advance Your Machine Learning Career

ML and AI colleagues, we have hand-picked five of the most valuable Machine Learning programs from our repository that can boost your career and earnings opportunities in the New Year. Some 2.7m+ students have enrolled in the Machine Learning Program from Stanford University. Next, the Microsoft Principles of Machine Learning course is part of the Microsoft Professional Program for AI. For a vendor-neutral approach the Machine Learning Specialization from the University of Washington receives high marks in the industry. The Applied Machine Learning Algorithms with Python program will strengthen your programming and mathematics skills. For cloud computing professionals we have selected the Microsoft Cloud Data Science with Azure Machine Learning Certification program. Finally, with the explosive growth of Python code libraries we decided to include Machine Learning with PyTorch Training for you over-achievers. You may wish to enroll in or several of these programs based upon your career goals and skillset.   

Your success begins today, Lawrence Wilson - Artificial Intelligence Academy

Data Engineering with Python and AWS Lambda – Career and income success await you

Data Engineering colleagues, AWS Lambda is an event-driven, serverless computing platform provided by Amazon as a part of the Amazon Web Services. It is a computing service that runs code in response to events and automatically manages the computing resources required by that code. AWS Lambda supports securely running native Linux executables. Data Engineering with Python and AWS Lambda LiveLessons shows users how to build complete and powerful data engineering pipelines in the same language that Data Scientists use to build Machine Learning models. By embracing serverless data engineering in Python, you can build highly scalable distributed systems on the back of the AWS backplane. Users learn to think in the new paradigm of serverless, which means to embrace events and event-driven programs that replace expensive and complicated servers. This program will equip you to: Perform Data Engineering tasks on AWS, develop with Cloud9, Write AWS Lambda functions in Python, Implement cloud-native Data Engineering patterns, i.e. serverless, and Architect event-driven architectures on the AWS platform using SQS, Python Lambda, and other AWS technologies.

Enroll today at: https://tinyurl.com/y6ct4jzt   

Much career success, Lawrence Wilson – Artificial Intelligence Academy   

AWS Certified Machine Learning-Specialty (ML-S) – Your ticket to new ML career and earnings opportunities

AI and ML Pros, this program covers the essentials of Machine Learning on AWS and prepares a candidate to sit for the AWS Machine Learning-Specialty (ML-S) Certification exam. Four main categories are covered: Data Engineering, EDA (Exploratory Data Analysis), Modeling, and Operations. The course offers the following tools to help users pass the exam: Each lesson module includes a five-question multiple-choice quiz in the style of the AWS ML exam. There are 39 quizzes, with a total of 195 questions. Practice Exam: A multiple-choice practice exam is included in the style of the AWS ML exam. This exam totals 50 questions and takes one hour to complete. You Will Learn How to perform data engineering tasks on AWS* How to use Exploratory Data Analysis (EDA) to solve machine learning problems on AWS, How to perform machine learning modeling tasks on the AWS platform, How to operationalize machine learning models and deploy them to production on the AWS platform, as well as How to think about the AWS Machine Learning-Specialty (ML-S) Certification exam to optimize for the best outcome. Build high-demand skills via the following training modules: 1) AWS Machine Learning-Specialty (ML-S) Certification, 2) Data Engineering for ML on AWS, 3) Exploratory Data Analysis on AWS, 4) Machine Learning Modeling on AWS, 5) Operationalize Machine Learning on AWS, 6) Create a Production Machine Learning Application – AWS SageMaker, and 7) Case Studies including Sagemaker Features, DeepLense Features, Kinesis Features, AWS Flavored Python and Cloud9.

Register today at: https://tinyurl.com/wf3ffhl 

Career success awaits you,  Lawrence Wilson – Artificial Intelligence Academy   

Machine Learning with PyTorch Training – Take the next step in your professional and income growth

Software Developers and Engineers, this intermediate level course with over six hours of video instruction will equip you to Apply various machine and deep learning techniques, Understand the difference between various machine and deep learning libraries, create classifiers and Enhance an existing classifier. It begins with the basic concepts of machine and deep learning, then learn how it can be applied to some popular problem domains. Training modules include: 1) What Is Machine Learning? What Is Deep Learning? 2) Comparing Several Libraries, 3) Understanding PyTorch and using tensors, autograd, and NumPy interfaces, 4) Tasks with Networks such as feature classifiers, regression prediction, clustering, adversarial networks and speech tagger, and 5) Enhancing an Image Classifiers with torchvision models, retrain pretrained models, and modify network layers.

Why not enroll today? Visit: https://tinyurl.com/szmb6cl

Much career success,  Lawrence Wilson – Artificial Intelligence Academy   

Integrated Program in Big Data and Data Science Maters Certificate – Your gateway to new career & income potential

Colleagues, mastering the field of data science begins with understanding and working with the core technology frameworks used for analyzing big data. You’ll learn the developmental and programming frameworks Hadoop and Spark used to process massive amounts of data in a distributed computing environment, and develop expertise in complex data science algorithms and their implementation using R, the preferred language for statistical processing. The insights you will glean from the data are presented as consumable reports using data visualization platforms such as Tableau. The five courses in this program are: 1) Data Science Certification Training - R Programming, 2) Big Data Hadoop and Spark Developer, 3) Tableau Desktop 10 Qualified Associate Training, 4) Data Science with Python, and 5) Machine Learning. Electives include Data Science with SAS Training, Apache Spark and Scala, MongoDB Developer and Administrator, Apache Cassandra, and many more. Much career success,  Lawrence Wilson – Artificial Intelligence Academy   

Why not enroll today? Visit: https://tinyurl.com/yxvxgaq2

Artificial Intelligence Engineer Master's Course – Accelerate your AI career & earnings growth

Attention Software Engineers and Data Scientists, this comprehensive master's course will equip to become a certified Artificial Intelligence Engineer. This training will help you learn various aspects of AI like Machine Learning, Deep Learning with TensorFlow, Artificial Neural Networks, Statistics, Data Science, SAS Advanced Analytics, Tableau Business Intelligence, Python and R programming and MS Excel through hands-on projects. As a part of online classroom training, you will receive 5 additional self-paced courses co-created with IBM namely Machine Learning with Python, Deep Learning with TensorFlow, Build Chatbots with Watson Assistant, R for Data Science, and Python. Moreover, you will also get an exclusive Access to IBM’s Cloud Platforms which are Cognitive Classes and IBM Watson Cloud Lab. You will gain high-demand skills in each of the training modules below: 1) Introduction to Artificial Intelligence domain, 2) How Data Science and Artificial Intelligence overlap, 3) Importance of Python coding for data analytics, 4) Efficient design of Machine Learning systems, 5) SAS tool for data analytics, modeling and visualization, 6) Working with Tableau interactive dashboard and reports, 7) MS Excel calculations, tables and formulae, 8) R Statistical computing for Data Science, 9) Building of Artificial Neural Networks and Statistical Models, and 10) Deep Learning techniques and working with TensorFlow. Much success, Lawrence Wilson – Artificial Intelligence Academy   

Get started today. Enroll at: https://tinyurl.com/r9cnbry       

Top 3 Strategies for 2020 to Advance Your Python Software Career

Software Developers and Engineers, do you want to increase your income and career potential in the New Year? If so, we can help. Here are three proven strategies that can boost your success. First, Get Trained. Here are three of the best training programs we have uncovered: Programming with Python for Data Science, Machine Learning with PyTorch, and Applied Machine Learning Algorithms with Python.  Second, Get Published: Use the Write an Article tools in your Linked In home page. Join and publish an article to the Python group on Reddit (480k members). Submit an article to Mention (click here for 5 tips on getting your article accepted). And third, Get Known: Establish yourself as an Influencer on Triberr (join for free). Join the Facebook Python Developers Group with 138k members. Finally, interact with the 1.4m members on the Google AI community on Twitter.

Programming with Python for Data Science: https://tinyurl.com/skcgkkq     

Machine Learning with PyTorch: https://tinyurl.com/yx6bxeth

Applied Machine Learning Algorithms with Python: https://tinyurl.com/r2jegmz

Much success, Lawrence Wilson – Artificial Intelligence Academy