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Introduction:   A collection of methods and strategies called machine learning algorithms are employed to create computer models that can learn from data. In many industries, these algorithms provide forecasts, spot patterns, and automate processes. The best machine learning methods and use cases will be covered in this article. It will also detail how these techniques might enhance forecast accuracy, task optimization, and Decision-making.   Types of Machine‌ ‌Learning Algorithms   1. SVM algorithm 2. Linear regression 3. Logistic regression 4. Decision tree 5. KNN algorithm 6. Random forest algorithm   SVM algorithm:   SVMs are effective supervised machine learning algorithms that can be applied to classification and regression issues. A kernel function translates the data points into a higher dimensional space, allowing for a more precise classification after determining the best hyperplane to divide the data points into two classes. The SVM approach is frequently used in applications including facial recognition, text classification, and picture identification and may also be used to find outliers in datasets. SVM has become one of the most well-liked machine learning algorithms today due to its high performance in various applications. Linear regression:   A statistical approach known as linear regression is used to model the relationship between one or more independent variables and a dependent variable. It is extensively used in many disciplines, including economics, engineering, and medicine. Foreseeing how certain occurrences will turn out assists us in better understanding how a system behaves. Based on historical data, linear regression can be used to forecast future results. As a result, it is an effective tool for anticipating and making decisions. Additionally, it can be used to spot patterns in data sets that other methods missed. To reveal important insights into complex systems that would otherwise remain hidden, linear regression requires a grasp of the underlying relationships between variables.   Logistic regression:   A powerful machine learning method for predicting the likelihood of an outcome is logistic regression. It is employed in various tasks, including picture classification and customer churn prediction. It functions by utilizing existing data to create a model that can be applied to forecast upcoming occurrences or results. Binary and multi-class classification issues can both be solved using logistic regression, as well as regression issues. One of the most well-liked machine learning algorithms is the logistic regression technique since it is straightforward to comprehend. Insights into complicated systems that otherwise would not be known.    Decision tree:   Data scientists can make decisions and forecasts using decision trees, an effective technique. Data scientists can discover the most crucial elements in a situation and choose the best course of action by using them to model complex decision-making scenarios. Decision trees have many uses, including anticipating stock prices and customer behavior. Businesses can improve their decisions and prediction accuracy by using decision tree algorithms. KNN algorithm:   An approach for classification and regression in supervised learning is called K-Nearest Neighbours (KNN). Since it is non-parametric, no assumptions are made on the underlying data. KNN labels a given point by first locating the k-nearest data points and then assigning the majority of those points' labels to it. Because of this, it is the perfect algorithm for jobs like anomaly detection, recommendation systems, and picture identification. With this algorithm, we can anticipate outcomes based on fresh data utilizing the knowledge we have gained from our training dataset.   Random forest algorithm:   An ensemble learning technique called the random forest algorithm makes predictions using several decision trees. The approach is supervised and may be applied to classification and regression applications. The approach builds numerous decision trees based on a subset of attributes randomly chosen from the dataset. The average of each decision tree's predictions is used for the final forecast. Due to their accuracy, robustness, and scalability, random forest algorithms are frequently employed in numerous fields. In addition to many other things, it can estimate stock prices, identify credit card fraud, and predict customer attrition. It has developed into one of the most effective tools for handling high-dimensional data collections thanks to. 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In February 2021, Representative Marjorie Taylor Greene of Georgia was dealt what would typically be considered a knockout blow in Washington politics: She lost her seats on House committees, where Congress does much of its work, because she had supported the QAnon conspiracy theory and spread other dangerous misinformation on social media.   But instead of being consigned to political oblivion, Greene has gained clout over the past two years, as my colleague Robert Draper explained in a New York Times Magazine profile of her that published online this morning.   Last month, Greene sat directly behind the House minority leader, Kevin McCarthy, as he unveiled his agenda for the midterm elections. Republican candidates often ask Greene to campaign for them. She has become a major fund-raiser within the party. And Greene told Robert she had talked with Donald Trump about being his running mate if he were to run for president in 2024.   “This is not at all what I expected when I began reporting on Greene,” Robert told me.   So how did Greene, who was a political pariah a few years ago, place herself at the center of Republican politics today? Read more   rory eleanor taylor

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In this guide we will show you how to fix a stuck explorer and start it back up after a node reboot. NOTE: The folders, commands and locations noted in this guide are for explorers set-up by NerdLabs001 some locations and commands may be different on your node, but we will try to cover the basics that will work on all Iquidius explorers. You will need a SSH client, everything can be done through the SSH Client with commands this will be covered in this guide. There are many SSH clients to choose from feel free to use the one your are most comfortable with, SSH for windows users Putty is available as a free client if you don't have one, Linux and Mac both have built in ones you can use.   NOTE: The ## notes the line of code you will enter do not type the ##.   Fix a stuck Iduidius Explorer SSH onto the node using the recommended way per your client.  First you will need to stop the explorer, if your explorer is using forever instead of screen see below ( Using Forever )    ## screen -r -d (this will take you to the running explorer) ## Ctrl c (to stop explorer) ## cd tmp ## ls (you are looking for index.pid and/or delete.me you will need to remove both) ## rm index.pid (then again for delete.me if its there (i.e.. rm delete.me) ## cd .. ## npm start (You can wait for cronjob to kick in just to make sure it has started updating - you will see lots of numbers scroll past the screen really fast if its updating :grinning: ) Close the SSH client you are done.   Using Forever ## forever list  ## forever stop (then name of process the 4 char one) ## npm stop ## cd tmp ## ls (you are looking for index.pid and/or delete.me you will need to remove both) ## rm index.pid (then again for delete.me if its there (i.e.. rm delete.me) ## cd .. ## forever start -c "npm start" ./  ( this starts the explorer ) Close the SSH client your are done.   Restart a Explorer after a node reboot SSH onto the node using the recommended way per your client. ## cd run ## ./coind -daemon -reindex -txindex (this starts the daemon for the explorer - (may have to press enter after to get the command prompt back) ## cd .. ## sudo systemctl start mongod (it may ask for the password of the root user-same password used to ssh in) ## cd explorer ## cd tmp ## ls (you are looking for index.pid and/or delete.me you will need to remove both - in this step they may not be there but it is good to check before we move on if they are not there skip next step ( i.e.. rm index.pid) ## rm index.pid (then again for delete.me if its there (i.e.. rm delete.me) ## cd .. ( if using forever see Using Forever to start explorer back up ) ## screen ( then hit enter to get past the text that pops up if it does )  ## npm start  Close the SSH client you are done.    

I decided when finding a solution to a build issue its nice to share it . we all save eachother time by contriputing.

How do i deal with a makefile.am This solution finally worked for me    only thing you have to do (mostly) is to just run ./configure, then make, then make install to install the software to a default location. If you want to change configure options, you can also look at ./configure --help.

Introduction to compiling coins in Linux This GUIDE NEEEEEED UPDATED    This guide is will get you started using Linux in an easy to follow manner. For the moment Ubuntu 16 is still the most compatible distro. We will be using Ubuntu 16.o4 Desktop for this demonstration but this guide does apply to most distros.   Prerequisites * Computer with an installation of Linux on it (seriously that's it) Let's begin the first thing you will need to do is find the link to you Terminal sometimes Known as the command prompt, bash, ect . It's a good idea to drag the Terminal launcher to your Launch bar. it should also be noted that you can right-click inside of any directory and select open in terminal. The next thing we're going to do is enter some commands to update our install. I will make all commands Italic as you get more familiar with Linux some of this will be memorized.   First, we're going to run sudo apt-get update Next sudo apt-get upgrade if you are prompted for yes/no just hit the Y key Note you can hit up on the keyboard to see past commands.   The next thing we're going to do is head over to the Litecoin Github to get some more commands from the Linux/Unix Documentation. Most coins will build for you without a fight after installing the Litecoin Dependencies. It's best to grab this next part from their page as they keep it updated. you want to scroll down to  Linux Distribution Specific Instructions https://github.com/litecoin-project/litecoin/blob/master/doc/build-unix.md ATT there are instructions for multiple Linux distros on this page  we only want the dependencies for ubuntu. NOTE:  After  sudo add-apt-repository ppa:bitcoin/bitcoin you will need to press enter to accept    EXTRA NOTE: sudo apt-get install qt4-qmake AND sudo apt-get install libqt4-dev AND sudo apt-get install libboost-all-dev   Will be needed for a good portion of altcoins including this one  but have been recently removed from the Litecoin readme     Its a good idea to go ahead and grab the optional downloads  also for qt4 qt5 you will need them from time to time.    If that all went ok as planned its time to pick an altcoin to build. for this demonstration ill be using Flapx it builds pretty easy. source files can normally be found by typing the name of the coin and GitHub into a search. It's best to try the official page first to make sure you have the correct link. Before we start building it is a good idea to lay out a folder or two.   Personally, i use 3 folders.   A lab folder to do my compiling in . A run folder to keep the built coins in  A folder to keep both those in my case its named nerdhome   NOTE: its best to keep things lowercase so you don't have  to guess later on how you named something.     Enter your lab folder or whatever you chose to name the directory. Nows a good opportunity to try out that open in terminal option.   On a fresh install of linux, you will need to install git do that with the following command  sudo apt install git Flapxcoin is located https://github.com/FlapXCoin/flapxcoin So what we need to do to get our a copy the proper way is type in the terminal or copy paste   git clone https://github.com/FlapXCoin/flapxcoin Now you should have your own copy of flapxcoin.   From here you can enter the root of flapxcoin by typing. cd flapxcoin or you may open a new from inside the folder. We will be building the GUI of the wallet first using qt. we need to start that buy running qmake in the terminal I want to explain this next command if you ignore this part you may crash your compilation. So at this point, we could just type in make and several moments later our new wallet should appear. using make alone only uses one core of your cpu and can take a really really ...... really long time. What im going to fo on my system is tell it to use 6 cores. I will do this by typing  make -j6 this will build literally 6 times faster in most cases NOTE every core would like to have 2GB of ram. so if i have only 4GB of ram and 4 cores and try to use make -j4 there is a chance my compilation will fail and I won't be sure why My current environment is 32GB of ram and 8 cores. since I'm doing other things at the moment that I prefer not to crash, I will be running  make -j6 its really up to your discretion you know your system better than anyone. also.. -j6 does not indicate cores it indicates threads. I am not on a multithreaded system but if I was I could run make -j16 providing I have the prescribed 32GB of ram   at this point, you should have yor flapx wallet built i need to sort a few things out in this guide i will finish it soon   

https://www.crypto-city.com/index.php/video/play/1224/nerdlabs-how-to-checkpoint-a-cryptocurrency-blockchain-featuring-elite-curr/