![]() ![]() British father, 51, is killed in 'high speed hit and run' while cycling in Italy.Meghan Markle avoids an awkward run-in with ex-best friend Jessica Mulroney as both women cross over in Las Vegas on the same weekend. ![]() Harry and Meghan take private plane to Vegas with actresses Cameron Diaz and Zoe Saldana and musician Benji Madden to watch Katy Perry in concert.Dazzling Duchess! Meghan Markle donned £5,576 Valentino dress and £585 Louboutin stilettos to watch fellow-Montecito resident Katy Perry's concert.Harry's not ready to Roar! Duke is spotted looking 'bored' as Meghan dances along to pal Katy Perry's hit at Vegas show - after flying in on a private jet with Cameron Diaz.The rise of the smashburger: How US craze for trendy patties costing up to £15 is taking over British high streets and replacing the humble burger in a bun.Up to 12,000 Brits are STILL without water as Thames Water supply crisis sparks chaos - with fears for care homes, schools forced to shut and locals queueing for bottled water in car parks after firm blamed the weather for shortage.Woman, 62, keyed top of the range cars in her village including a Mercedes and Range Rover Vogue causing thousands of pounds worth of damage because they were parked on the pavement and 'she was feeling menopausal'. ![]()
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![]() In my starting ship I was making about 65k per minute (depending on supply). The Thrusters sell for +1k each, and the Prostetics net a couple hundred. The stations are less than 30 seconds apart-even less if you pick up a Dynamo III enhancement from Alameda, and Navigation officer Rico Dempsey from Vigo. I found that when just starting out, I could make a decent profit by flying Thrusters and Prostetics back and forth between Plymouth Shipyard and MultiOps HQ near Soreen. I put all power into engines and have a few speed enhancements so I don't even need to get a freighter. Only probs is that even with the 45 cargo space, the stock doesn't replenish fast enough. Originally posted by xenoneo:There's very little info around about how to make money running freight.Ĭheers for that, I tracked down the area and mined it for some quick cash. It's all out there, don't assume it isn't. We have to test things out to find out where the money is, and share the information to help others. However, you can see that it is viable currently to make money quickly through trade right now. I read that eventually they'll add tooltips to show bases that will buy your inventory for more money, but that's not in yet. Mining runs probably would be most beneficial in a freightliner for sheer volume since sales inventory is limited in bases, handicapping a frightliners ability to get the most out of a run from just trade. Of course there's probably ore in high risk asteroids that are currently just as profitible as my trade lane or piracy. Gold for instance went as low as 100 to as high as 700, from just the handful of bases I checked at. Raw materials consistantly sold for less than complicated items like the mechs, cells, and ATRs, but the values did change drastically. I just make money quickly, while I complete freelance missions between said bases.Īs far as Mining goes, I kept some ore on me as I was scouting item values for a while. This means I don't waste any time searching for a ship to board or puling it into a garage. Since I'm already have PTE at full when I dock, as I leave I'm still going full speed. I plot a course while I am in the store, and when I get close enough to see the next base, I select to dock. To get to each base takes about 1min 30sec, as they are about 2 hexes apart. I make $94,050 every 3-4 minuites like this. Yes, when I wrote that I was using the starting ship. At the moment this is exactly what's preventing me from playing this game more :D I am actually waiting eagerly for mining-trading prices balances. No point in travelling 10-15 minutes to make 45k when I can just shoot down 2 randoms reds in 2 minutes and gain 50k to 100k in just selling the junk they drop (not to mention how much you'll gain if you manage to capture and tow their ship to port). As it is now is simply impossible to run a decent trade-mining business with a fair value-for-time ratio. Originally posted by Nyx:There's little information about trading simply because it is not fully implemented nor balanced yet. ![]() ![]() If you've found a good trade route, post it here to help other space truckers. There's probably another station around there that will take them for more and I'll let you know if I find it. ![]() I haven't found the best route for this next one yet, but I noticed ATR vehicles sell at Ruhr for 5187 and sell at Planet Fairuz for 5534. Side note: if you deliver goods and people while running goods you'll be friendly with the area very quickly. I was origionally selling the mechs to Sora, but a mission took me up to Astralis where I found a much better buyer. The items come back after you have purchased them all, but if you want to fill up before you come back, utility droids and hydroponics make about 500 profit each as well. ![]() (x45 is 46,800)īuy Energy Cells at Astralis for 5619 and sell them at DaVinci for 6669. The route is DiVinci Reasearch Complex, which is just to the left of Sora, to Astralis, which is just above Sora.īuy Combat mechs from DaVinci for 5496 and sell at Astralis for 6536. Here's one I found by the planet Sora, in the very top right of the map. 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Enjoy free shipping on orders over $99 get special perks and be the first to know about promotions and/or specials with our Pink Perks. We’re out to spread positivity and love, too. We’re here to empower women and to help them look their best. We believe that looking great and feeling your best isn’t just a nice idea, it’s something that is achievable every day. We think you’ll love what you see here in our super nice clothes for women, including tops, shorts, dresses, leggings and more.Īwesome Products with a Purpose As one of the fastest-growing online retailers of women’s clothing online, there is always something new and awesome to discover here - at everyday low prices you’ll love. Looking for a summery color like green, pink or sunny yellow? Perhaps you’re looking for an Americana-themed print, an earthy camo print or a ditzy floral fabric that will stand out in the crowd. Quickly narrow down your search by size, color, style or trend. 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The tire producer / manufacturer and Canadian Tire uses this fee to pay for the collection, transportation, and processing of used tires.ĬANADIAN TIRE® and the CANADIAN TIRE Triangle Design are registered trade-marks of Canadian Tire Corporation, Limited. ![]() ![]() △The tire producer / manufacturer of the tires you are buying, and Canadian Tire is responsible for the recycling fee that is included in your invoice. ![]() ![]() ![]() “Silo” is produced for Apple TV+ by AMC Studios and based on the novels by Hugh Howey. The ensemble cast starring alongside Ferguson includes Common (“The Chi”), Emmy nominee Harriet Walter (“Succession”), Chinaza Uche (“Dickinson”), Avi Nash (“The Walking Dead”), Critics Choice Award and NAACP winner David Oyelowo (“Selma”), Emmy nominee Rashida Jones (“Parks and Recreation”) and Academy Award winner Tim Robbins (“Mystic River”). Ferguson stars as Juliette, an engineer, who seeks answers about a loved one's murder and tumbles onto a mystery that goes far deeper than she could have ever imagined, leading her to discover that if the lies don't kill you, the truth will. However, no one knows when or why the silo was built and any who try to find out face fatal consequences. “Silo” is the story of the last ten thousand people on earth, their mile-deep home protecting them from the toxic and deadly world outside. In this week’s new episode, launching Friday on Apple TV+, “Hanna,” new information causes Juliette to see her family’s past differently - and she finally gains access to the silo’s biggest secrets. "Apple has believed in our vision from day one and it’s an honor to have the opportunity to dig deeper into this story and peel back the layers to our characters in the silo.” “We cannot wait for audiences around the world to immerse themselves in the epic world we have created to bring Hugh Howey’s novels to life,” said Yost. “As audiences around the world have become gripped by the mysteries and conspiracies buried within this fascinating subterranean world, viewership only continues to climb, and we are so excited for more secrets of the silo to be revealed in season two.” ![]() “It has been enormously fulfilling to see the engrossing, atmospheric and beautifully crafted sci-fi epic ‘Silo’ quickly become Apple’s number one drama series,” said Matt Cherniss, head of programming for Apple TV+. Since its global premiere on May 5, “Silo” was quickly hailed as a “riveting and equally star-studded,” “must-watch” series and “simply transcendent sci-fi TV.” Week-to-week, the series drives growing viewership and, in addition to quickly reaching Certified Fresh status on Rotten Tomatoes, has landed acclaim for its "rich and compelling” world-building elements, as well as the “incredible” performance by Ferguson, who “brings an understated gravitas” to the lead role. Created by Emmy-nominated screenwriter Graham Yost, who also serves as showrunner, and starring and executive produced by Rebecca Ferguson, the eighth episode of “Silo” premieres this Friday on Apple TV+. Apple TV+ today announced a season two renewal for “Silo,” the acclaimed, world-building drama based on Hugh Howey’s New York Times bestselling trilogy of dystopian novels. ![]() ![]() ![]() Post, Digital, Visual Effects (PDV) Incentive.Production Attraction Strategy (PAS) Incentive. ![]()
![]() “Athletes should try not to do strenuous exercise in the hours before bedtime when possible and allow enough time for food and liquids to be digested before sleep,” says Schlichter. ![]() And, you should be sure to give yourself time after your workout to prepare for sleep. “There’s not any evidence on sleepy teas specific to runners, but they can be used as one of many tools to help support relaxation and healthy sleep hygiene in athletes,” Schlichter says.įor example, if you find yourself energized after an afternoon or evening run, steeping a cup of sleepy tea may help kickstart the relaxation process. If you struggle with sleep, it may be worth a shot to implement a cup into your nightly routine. A variety of sleepy tea called Extra has valerian in it, and some studies have found that this herb can cause headaches, dizziness, and an upset stomach, Gans says. One ingredient in particular-valerian-may also cause some unwanted side effects. “Also, pregnant and nursing women and those suffering from low blood pressure may be more apt to risks and side effects and definitely want to check with a healthcare provider.” Celestial Seasonings Sleepytime Tea is a much-loved nighttime remedy of an herbal blend that includes chamomile, spearmint and tilia flowers, among others. “ Some people have reported allergies to some ingredients in herbal teas, like chamomile,” Schlichter says. It’s always best to check with your doctor before starting a regular routine. And, there are certain teas or ingredients you may want to avoid if you are taking certain medications. While chamomile is listed on the FDA’s list of ingredients generally recognized as safe (GRAS), some people may experience some side effects, like allergies. In general, sipping these teas regularly before bed is safe. The 7 Best Sleep Trackers To Optimize Your HealthĪre There Risks or Side Effects to Sleepytime Tea?.I suggest steeping it for up to five minutes before drinking,” Martin says. “The longer you allow to steep, the stronger it is. ![]() Keep in mind that to get the most out of your tea, steep time is critical. “Drinking a sleep tea afterwards can help calm you down so that you’re better able to fall and stay asleep.” “An evening cardio session gets your heart rate up and releases endorphins, making it difficult to wind down at night, possibly derailing your sleep,” says Martin. It can also be a great way to decompress after a nighttime workout. “For many people the ritual of drinking tea is relaxing, and it may cause sleepiness as a result,” Keri Gans, M.S., R.D.N., tells Runner’s World. And while science may back up the ingredients, it may also just be the act of tea drinking itself that induces the sleep. Another short-term randomized control trial of 40 healthy adults, published in 2013, found that those who drank a sleep tea daily (with standardized extracts of valerian root and passionflower) for one week reported better sleep quality than those who did not drink the tea. ![]() ![]() ![]() That is not meant to sound bigheaded in any way, but I honestly have never had any issues with this recipe in the entire time I have baked it.Īs I write this, its the day before the 30th of November, so all I can think about is how its ‘officially’ the festive season starting tomorrow, and how I can start munching on my advent calendars tomorrow.Įvery year, I bake gingerbread men to munch on, and they last a good while as well. I get several messages every year about what my favourite gingerbread biscuit recipe is and have I got anything to save the bakers from every other recipe they have tried, and this one is the solution. It’s not something I personally want to mess with any time soon! This sorta recipe is the perfect bake to top and decorate the gingerbread drip cake recipe I have, and my Christmas gingerbread cake recipe! A must try recipe I updated the photos for this post but the recipe has stayed the same. Also, the cookie cutters I have used for years are some my granny had, and the ‘female’ one was lost a long time ago… Needless to say, I could have just bought more, but I wanted to stick to traditions in my festive baking ways. ![]() Yes, I realise you are supposed to call these gingerbread biscuits, or gingerbread people these days, but I stuck with the classic name. I find it’s the perfect mix of all things spicy, and the biscuit is both crunchy and chewy at the same time which is what I am after in a gingerbread biscuit. I have tried other recipes and they have all gone so wrong – spreading so much they form a giant cookie, or being so crunchy I feel like my teeth will break – this recipe though, its the perfect mix of crunchy & chewy, and they don’t spread! The men actually still look like men when they come out of the oven!īut anyway, this recipe honestly is my go-to gingerbread biscuit recipe, I have never failed with it since I developed the recipe and it has been a massive hit with all of my taste testers over time. I have had my troubles with gingerbread over the years strangely enough, even if it seems like one of the most common Christmas bakes. The only other Christmassy biscuits I have on my blog already are my white chocolate & cranberry cookies and my chocolate orange cookies and others – and don’t get me wrong, both of these are delicious – however, they aren’t gingerbread men. I have been asking on my Facebook page recently what sort of Christmas themed recipes everyone wanted and this was 100% one of them – like so many people asked for it, I couldn’t not bake it – GINGERBREAD MEN! ![]() Please see my disclosure for more details!* A chewy & crunchy Christmassy biscuit that everyone will love to bake & decorate! ![]() ![]() ![]() Plt.plot(X_grid, regressor.Reading time: 30 minutes | Coding time: 10 minutes X_grid = X_grid.reshape((len(X_grid), 1)) # reshape for reshaping the data into a len(X_grid)*1 array, # Visualising the Random Forest Regression results Y_prediction = regressor.predict(np.array().reshape(1, 1)) # test the output by changing values Regressor = RandomForestRegressor(n_estimators = 100, random-state = 0) # Fitting Random Forest Regression to the datasetįrom sklearn.ensemble import RandomForestRegressor Step 4 : Fit Random forest regressor to the dataset Step 3 : Select all rows and column 1 from dataset to x and all rows and column 2 as y You will be using a similar sample technique in the below example.īelow is a step by step sample implementation of Rando Forest Regression. At this stage you interpret the data you have gained and report accordingly.If it doesn’t satisfy your expectations, you can try improving your model accordingly or dating your data or use another data modeling technique.Now compare the performance metrics of both the test data and the predicted data from the model.Provide an insight into the model with test data.Set the baseline model that you want to achieve.Specify all noticeable anomalies and missing data points that may be required to achieve the required data.Make sure the data is in an accessible format else convert it to the required format.Design a specific question or data and get the source to determine the required data.We need to approach the Random Forest regression technique like any other machine learning technique We randomly perform row sampling and feature sampling from the dataset forming sample datasets for every model. Random Forest has multiple decision trees as base learning models. The basic idea behind this is to combine multiple decision trees in determining the final output rather than relying on individual decision trees. This part is Aggregation.Ī Random Forest is an ensemble technique capable of performing both regression and classification tasks with the use of multiple decision trees and a technique called Bootstrap and Aggregation, commonly known as bagging. In the case of a regression problem, the final output is the mean of all the outputs. In the case of a classification problem, the final output is taken by using the majority voting classifier. Principal Component Analysis with PythonĮvery decision tree has high variance, but when we combine all of them together in parallel then the resultant variance is low as each decision tree gets perfectly trained on that particular sample data and hence the output doesn’t depend on one decision tree but multiple decision trees.Introduction to Dimensionality Reduction.Genetic Algorithm for Reinforcement Learning : Python implementation.Reinforcement Learning Algorithm : Python Implementation using Q-learning.Implementing Agglomerative Clustering using Sklearn.Hierarchical clustering (Agglomerative and Divisive clustering).OPTICS Clustering Implementing using Sklearn.Implementing DBSCAN algorithm using Sklearn.DBSCAN Clustering in ML | Density based clustering.Mini Batch K-means clustering algorithm.Analysis of test data using K-Means Clustering in Python.Elbow Method for optimal value of k in KMeans.Different Types of Clustering Algorithm.Types of Learning – Unsupervised Learning.Decision tree implementation using Python.Decision Tree Introduction with example.Using SVM to perform classification on a non-linear dataset.SVM Hyperparameter Tuning using GridSearchCV.Support Vector Machines(SVMs) in Python.Why Logistic Regression in Classification ?.Implementation of Polynomial Regression.Boston Housing Kaggle Challenge with Linear Regression.A Practical approach to Simple Linear Regression using R.Multiple Linear Regression using Python.Linear Regression (Python Implementation).Mathematical explanation for Linear Regression working.Momentum-based Gradient Optimizer introduction.Optimization techniques for Gradient Descent.Mini-Batch Gradient Descent with Python.Gradient Descent algorithm and its variants.Types of Learning – Supervised Learning.Basic Concept of Classification (Data Mining).Handling Imbalanced Data with SMOTE and Near Miss Algorithm in Python.Data Preprocessing for Machine learning in Python.Generate test datasets for Machine learning.Difference between Machine learning and Artificial Intelligence.Machine Learning and Artificial Intelligence.Introduction to Data in Machine Learning.How is Data important in Machine Learning.How can I get started with Machine Learning.Machine Learning – the beginning of new Era. ![]() |
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