116 Educators providing Forest courses in London

Python Machine Learning algorithms can derive trends (learn) from data and make predictions on data by extrapolating on existing trends. Companies can take advantage of this to gain insights and ultimately improve business. Using Python Machine Learning scikit-learn, practice how to use Python Machine Learning algorithms to perform predictions on data. Learn the below listed algorithms, a small collection of available Python Machine Learning algorithms.

Python Data Analytics boot camp. 12 1 day lessons, learn Python Basics through to machine learning and front-ends. With practical project to give you full confidence and credibility.

This Python Machine Learning online instructor led course is an excellent introduction to popular machine learning algorithms. Python Machine Learning 2-day Course Prerequisites: Basic knowledge of Python coding is a pre-requisite. Who Should Attend? This course is an overview of machine learning and machine learning algorithms in Python SciKitLearn. Practical: We cover the below listed algorithms, which is only a small collection of what is available. However, it will give you a good understanding, to plan your Machine Learning project We create, experiment and run machine learning sample code to implement a short selected but representative list of available the algorithms. Course Outline: Supervised Machine Learning: Classification Algorithms: Naive Bayes, Decision Tree, Logistic Regression, K-Nearest Neighbors, Support Vector Machine Regression Algorithms: Linear, Polynomial Unsupervised Machine Learning: Clustering Algorithms: K-means clustering, Hierarchical Clustering Dimension Reduction Algorithms: Principal Component Analysis Latent Dirichlet allocation (LDA) Association Machine Learning Algorithms: Apriori, Euclat Other machine learning Algorithms: Ensemble Methods ( Stacking, bagging, boosting ) Algorithms: Random Forest, Gradient Boosting Reinforcement learning Algorithms: Q-Learning Neural Networks and Deep Leaning Algorithms: Convolutional Network (CNN) Data Exploration and Preprocessing: The first part of a Machine Learning project understands the data and the problem at hand. Data cleaning, data transformation and data pre-processing are covered using Python functions to make data exploration and preprocessing relatively easy. What is included in this Python Machine Learning: Python Machine Learning Certificate on completion Python Machine Learning notes Practical Python Machine Learning exercises and code examples After the course, 1 free, online session for questions or revision Python Machine Learning. Max group size on this Python Machine Learning is 4. Refund Policy No Refunds

This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, follow a methodical workflow to develop sound solutions, use open-source, off-the-shelf tools to develop, test, and deploy those solutions, and ensure that they protect the privacy of users. This course includes hands-on activities for each topic area.

Microsoft Active Directory course description A thorough understanding of this system is essential for anyone managing enterprise MS networks. Essential theory is complimented with a high level of hands on practice allowing delegates to observe the idiosyncrasies of Active Directory and Group Policy at first hand. Delegates learn the fundamental theory of AD and progress onto building a multi-domain network in the classroom. The course includes troubleshooting methods, and essential maintenance procedures. This course is designed to teach you the skills needed for day to day management of these technologies. What will you learn Install AD on multiple PCs. Use the tools to create and manage objects. Create appropriate group policies to restrict selected user's desktops and network access. Install DNS to support Active Directory without loosing Internet Connectivity. Maintain and troubleshoot AD problems Backup Active Directory. Microsoft Active Directory course details Who will benefit: Technical staff working with AD based networks. Prerequisites: Supporting Windows server. Duration 3 days Microsoft Active Directory course contents Introduction to Active Directory Network authentication methods, Active Directory defined, AD naming conventions, network management with AD, AD structures: Domains, Organisational Units, Forests & Trees, Sites, The Global Catalogue. Windows 2003 new features, installing AD. Hands on Installing an AD network. Windows overview Management methods Server management tools, installing the additional tools, Terminal Server: Administration mode, Administrator accounts in AD, Local Security Policy. Hands on Install the management tools, Management using Terminal Services. Creating & Managing Objects (a quick look) AD management tools, AD users and computers, Creating & managing OUs, User Accounts and groups, controlling access to AD objects, moving objects, Publishing resources, locating objects in AD, delegating authority. Hands on Creating a control OU structure and delegating authority. Introduction to Group Policies What are Group Policies? Where Group Policy data is stored, security, Group Policy flow. Hands on Implementing Group Policies Working with Group Policies Local security templates, administrative templates, scripts, folder redirection, software deployment. Hands on Scripts, redirecting the start menu, creating a secure, robust desktop environment. Implementing DNS DNS basics, troubleshooting, implementing DNS zones. Hands on Building a unified DNS solution. Maintaining and managing the AD database AD support tools, database internal structure, replication, replication tools, Single Operations Masters, tools for maintenance, maintenance techniques, Backing up AD, Directory Services restore mode, NTDSUtil, Authoritative & non-authoritative restoration, rebuilding. Hands on NTDSUtil.

An immersive and creative cross curricular experience with art, drama, science and exploration.

Forest Bathing, nature therapy and healing in the natural environment This is a time when we are all hearing the call to be out in the natural environment, becoming natural environment returners.