Natural Language Processing Engineer with Python Certification

Software colleagues, this Natural Language Processing Engineer with Python program will take you through the essentials of text processing all the way up to classifying texts using Machine Learning algorithms. You will learn various concepts such as Tokenization, Stemming, Lemmatization, POS tagging, Named Entity Recognition, Syntax Tree Parsing and so on using Python’s most famous NLTK package. Once you delve into NLP, you will learn to build your own text classifier using the Naïve Bayes algorithm. This course is for anyone who works with data and text– with good analytical background and little exposure to Python Programming Language. It is designed to help you understand the important concepts and techniques used in Natural Language Processing using Python Programming Language.  You will be able to build your own machine learning model for text classification. Towards the end of the course, we will be discussing various practical use cases of NLP in python programming language to enhance your learning experience. You will gain high demand, marketable skills in: 1) Introduction to Text Mining and NLP, 2) Extracting, Cleaning and Pre-processing and Machine Learning, 3) Analyzing Sentence Structure, 3) Text Classification – I & II, and 4) In Class Project on Sentiment Classification.

Register today at: https://fxo.co/8m2j 

Career success awaits you, Lawrence Wilson – Artificial Intelligence Academy (AIA)

Machine Learning Engineer Training ($130k+ average salary)

ML colleagues, according to ZipRecruiter Machine Learning Engineers earn $130,530 per year. Learn advanced machine learning techniques and algorithms -- including how to package and deploy your models to a production environment. Gain practical experience using Amazon SageMaker to deploy trained models to a web application, evaluate the performance of your models, A/B test models and update the models as you gather more data..Suggested prerequisites are intermediate knowledge of Python and Machine Learning algorithms. The four skill-based training modules (each with a unique training project) include: 1) Software  Engineering Fundamentals (Project: Build a Python Package), 2) Machine  Learning in Production with Amazon SageMaker (Project: Deploy a Sentiment Analysis Model), 3) Machine Learning Case Studies (Project: Plagiarism Detector), and 4) Machine Learning Capstone (Project: Select a machine learning challenge and propose a possible solution). 

Enroll today at: https://fxo.co/9glo 

Much career success, Lawrence E. Wilson - Artificial Intelligence Academy (AIA) 

Machine Learning Program with Andrew Ng (Stanford University)

ML colleagues, join over 3.5m students enrolled in this foundational program on machine learning, datamining, and statistical pattern recognition. Topics include: (i) Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks). (ii) Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning). (iii) Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI). Also learn how to apply learning algorithms to building smart robots (perception, control), text understanding (web search, anti-spam), computer vision, medical informatics, audio and database mining, Training modules include: 1) Linear Regression (single variable) and Algebra, 2) Linear Regression (multivariate) and Octave/Matlab Tutorial, 3) Logistic Regression and Regularization, 4) Neural Networks: Representation, 5) Neural Networks: Learning, 6) Advice for Applying Machine Learning and Machine Learning System Design, 7) Support Vector Machines, 8) Unsupervised Learning and Dimensionality Reduction, 9) Anomaly Detection and Recommender Systems, 10) Large Scale Machine Learning and 11) Application Example: Photo OCR.

Enroll today at: https://tinyurl.com/yxagguo8 

Much career success, Lawrence E. Wilson  - Artificial Intelligence Academy (AIA) 

Data Science with Python Specialization (University of Michigan)

Data Science colleagues, join over 217,000 professionals who have achieved their Applied Data Science with Python Specialization. This skills-based specialization is intended for learners who have a basic Python or programming background, and want to apply statistical, machine learning, information visualization, text analysis, and social network analysis techniques through Python toolkits such as pandas, matplotlib, scikit-learn, nltk, and networkx to gain insight into their data. Gain high-demand skills in Text Mining, Python Programming, Pandas, Matplotlib, Numpy Data Cleansing, Data Virtualization and  Visualization (DataViz), Machine Learning (ML), Algorithms, Machine Learning, Scikit-Learn, and Natural Language Toolkit (NLTK). The five courses which comprise this Specialization include: 1) Data Science in Python, 2) Plotting, Charting and  Data Representation in Python, 3) Machine Learning in Python, 4) Text Mining in Python, and 5)  Social Network Analysis in Python. 

Enroll today at: https://tinyurl.com/y2k3pq6u 

Much career success, Lawrence E. Wilson - Artificial Intelligence Academy (AIA) 

AI and Deep Learning with TensorFlow

AI and Deep Learning in TensorFlow with Python Certification Training master the concepts of SoftMax function, Autoencoder Neural Networks, Restricted Boltzmann Machine (RBM) and work with libraries like Keras & TFLearn. Gain high-demand skills in Deep Learning and TensorFlow Concepts, Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), Keras, TFlearn, Autoencoders, Restricted Boltz-mann Machine (RBM), Neural Networks & Natural Language Processing (NLP), Python with TensorFlow Libraries, Text Analytics and Processing.  Training modules include: 1) Introduction to Deep Learning, 2) Neural Networks with TensorFlow, 3) Deep Networks, 4) Convolutional Neural Networks (CNN), 5 )Recurrent Neural Networks (RNN), 6) Restricted Boltzmann Machine (RBM) and Autoencoders, 7) Keras API, 8) TFLearn API, and 9) In-Class Project.

Register today at: https://fxo.co/9PYj  

Much career success, Lawrence E. Wilson - Artificial Intelligence Academy (AIA) 

Python Spark Certification Training using PySpark (CCA175)

Big Data Architects, Engineers and Developers - PySpark Certification Training will equip you to become a successful Spark Developer using Python and pass the Cloudera Hadoop and Spark Developer Certification Exam (CCA175). Gain in-depth knowledge of Apache Spark and the Spark Ecosystem including Spark RDD, Spark SQL, Spark MLlib and Spark Streaming and acquire comprehensive knowledge of Python Programming language, HDFS, Sqoop, Flume, Spark GraphX and Messaging System such as Kafka. Skill-based training modules cover: 1) Big Data Hadoop and Spark, 2) Python for Apache Spark, 3) Functions, OOPs, and Modules in Python, 4) Apache Spark Framework, 5) Spark RDDs, 6) DataFrames and Spark SQL, 7) Machine Learning using Spark MLlib, 8) Spark MLlib - Deep Dive, 9) Apache Kafka and Apache Flume, 10) Apache Spark Streaming - Processing Multiple Batches and Data Sources, 11) Implementing an End-to-End Project, and 12) Spark GraphX.

Enroll today at: https://fxo.co/9YCB

Much career success, Lawrence E. Wilson - Artificial Intelligence Academy (AIA)

Deep Learning Specialization

Colleagues, join over 454k+ students worldwide who have learned the foundations of Deep Learning, build neural networks, and lead successful machine learning projects. This program will equip you in Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization and beyond. You will work on case studies from health care, autonomous driving, sign language reading, music generation and natural language processing (NLP). Master theory and see how it is applied in industry using Python and in TensorFlow. Build core skills in TensorFlow, Convolutional Neural Network, Artificial Neural Network, Deep Learning, Back propagation, Python Programming, Hyperparameter Optimization, Machine Learning, Inductive Transfer, Multi-Task Learning and Facial Recognition Systems. Training modules address: 1) Neural Networks and Deep Learning, 2) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization, 3) Structuring Machine Learning Projects, 4) Convolutional Neural Networks, and 5) Sequence Models.

Get started today: https://tinyurl.com/y2us98q9

Much career success, Lawrence E. Wilson - Artificial Intelligence Academy (AIA)

Advanced Deployment Scenarios with TensorFlow

ML colleagues, earn how to get your machine learning models into the hands of real people on all kinds of devices. Start by understanding how to train and run machine learning models in browsers and in mobile applications. Learn how to leverage built-in datasets with just a few lines of code, learn about data pipelines with TensorFlow data services, use APIs to control data splitting, process all types of unstructured data and retrain deployed models with user data while maintaining data privacy.  Gain advanced skills in: TensorFlow Serving, Machine Learning, Federated Learning, TensorFlow Hub, TensorBoard. Training modules cover: 1) TensorFlow Extended, 2) Pre-trained models with TensorFlow Hub, 3) TensorBoard: Tools for Model Training and 4) Federated Learning.

Enroll today at: https://tinyurl.com/yyuua8lc

Much career success, Lawrence E. Wilson - Artificial Intelligence Academy (AIA)

Amazon Machine Learning (Training)

ML colleagues, this Amazon Machine Learning includes over 20 independent lessons totaling more than 3 hours of instruction with demos, interactive hands-on labs and detailed slide explanations. You will be equipped to solve for personalization, search, marketing, finance, productivity, and management efficiency using AML, configure a schema, and set up a data source using “small data” in S3, use data insights and visualization tools, leverage Features, Targets, Observations, Labeled Data, Unlabeled Data, and Ground Truth to prepare historical data for predictive analysis, and prepare data for use in a regression model and a multi-class model. Skill-based training modules address: 1) Machine Learning Basics, 2) Machine Learning Data Architecture, 3) Data and Schema Configuration, 4) Visualization and Modeling, and 5) Predictions with Amazon Machine Learning. Hands-on labs Usage scenarios are provided to inspire viewers to create their own value-added services on top of Amazon Machine Learning.

Enroll today at: https://tinyurl.com/y3krtokl

Much career success, Lawrence E. Wilson - Artificial Intelligence Academy (AIA)

Python for Data Science Certification

Data Science colleagues, this Python Certification Training not only focuses on fundamentals of Python, Statistics and Machine Learning but also helps one gain expertise in applied Data Science at scale using Python. The training is a step by step guide to Python and Data Science with extensive hands on. The course is packed with several activity problems and assignments and scenarios that help you gain practical experience in addressing predictive modeling problem that would either require Machine Learning using Python. Starting from basics of Statistics such as mean, median and mode to exploring features such as Data Analysis, Regression, Classification, Clustering, Naive Bayes, Cross Validation, Label Encoding, Random Forests, Decision Trees and Support Vector Machines. Gain skills that will strengthen your career and equip you to pass the certification exam, including: 1) Sequences and File Operations, 2) Deep Dive – Functions, OOPs, Modules, Errors and Exceptions, 3) NumPy, Pandas and Matplotlib, 4) Data Manipulation, 5) Machine Learning with Python, 6) Supervised Learning, 7) Dimensionality Reduction, 8) Unsupervised Learning, 9) Association Rules Mining and Recommendation Systems, 10) Reinforcement Learning, 11) Time Series Analysis, plus 12) Model Selection and Boosting.

Register today at: https://fxo.co/9QE9

Much career success, Lawrence E. Wilson - Artificial Intelligence Academy (AIA)