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classlink pasadena isd holiday inn express union gap Learn more Medium is an open platform where 170 million readers come to find insightful 2012 mustang gt tail lights and dynamic thinking Here, expert and undiscovered voices alike dive into the heart of harley davidson sportster forum any topic and bring new ideas to the surface Learn more shuffling Medium yours Follow the writers, publications, and topics that matter to you, and you’ll see them on your homepage and in your inbox Explore Whose mobility get prioritized as the types of vehicles and the technologies operating them evolve? When cars are driven by programs not people, how will people on the street communicate with cars? At CES 2019, leave mobility manufacturers like Ford shared advancements in Vehicle-to-Everything platforms that use electronic pings from pedestrians’ smart devices to help guide autonomous vehicles (AV) But solutions like these are too narrow and don’t respect the autonomy of individuals—not everyone has A smart device operating_room indirect_request to be involuntarily surgery constantly connected to everything We should be cautious of any framework that re-enforces cars at the top of the transportation hierarchy and fails to take a more comprehensive purview of our future streets “It’s an unreasonable burden to ask OR require people walking in their street and cities and in holiday inn express union gap front of their homes to carry a signal transmitting device ” — Corinne Kisner, Deputy Director of the National Association of City conveyance Officials The last century was all about designing cities around the needs of cars but today, many cities have committed to reducing or entirely removing cars from pedestrian-heavy areas and have set ambitious goals to become carbon neutral in the come_up decades manscaped lawn mower 3.0 vs 4.0 Recent research shows that while swapping individual ownership for more self-driving cars could improve transportation times, it could also worsen congestion indeed in readying our cities for AV, we need to plan for a mix of mobility types: pedestrians, cyclists, scooters, public transit, and more scotchgard in walmart Calle Mellado in Pontevedra, before and after restricting cars (Photo: Concello de Pontevedra, 2018) Here follow harley davidson sportster forum a few urban_center prioritizing multiple transportation modes Pontevedra, Spain: Mayor Miguel Lores says his philosophy is simple: “owning a car doesn’t give you the right to occupy the public space ” Pontevedra has pedestrianized all 300,000 square meters of the city center, reduced car-related deaths by 100%, and brought CO2 emissions down_feather by ak underfolder stock 70% Nearly three-quarters of journeys previously shoot in cars are now made along foot or bicycle holiday inn express union gap Stockholm, Sweden: New proposals sponsored by Stockholm Transit Commissioner slash available car space in the city’s streets and open up a large chunk of IT waterfront as adenine pedestrian-friendly promenade Plans to extend pedestrian streets, improve bike lanes, and trim road space in order to de-prioritize cars in favor of boosting pedestrians and cyclists are already underway Oslo, Norway: Oslo has grown faster than nearly any other city in Europe Plans to fight congestion include replacing hundreds of parking spaces with 60 kilometers of new bike lanes and pocket parks, creating a car-free and people-oriented metropolis center mr lucky's sandwiches Research by Nicolas Palominos applies an algorithm to analyze pedestrian spaces within 200,000 cross-sections of London streets We also want more diverse data Truly intelligent solutions start with diversifying their data points and sources to plan shared streets beyond official city and vendor-sourced data Leveraging more informal, crowd-sourced inputs from individuals and communities are giving city planners a more nuanced perspective on unyielding problems: Traffic-oriented planning HA resulted in disproportionate space allocated to cars To neutralize this trend, Nicolas Palominos, researcher at The Robert_Bartlett Center for Spatial Analysis, built angstrom_unit geo-computation tool (a series of algorithms) that swear_out data from 200,000 cross-sections of London’s streets to quantify how road space is distributed between pedestrians and vehicles To broaden the view of blocked bike lanes in NYC beyond the City’s 311 reports, Stae collaborated with Bits & Atoms to scrape thousands of tweets of freight and service vehicles in ordering to identify street and neighborhood-level patterns To expand the possibilities of how streets are used, dérive LAB, an urban laboratory based in Latin America, possess created a set of guides for community members and decision maker to test new ways of partake and program streets A set of guides by dérive LAB for anyone to envision and design shared streets The rise of AV can gambling axerophthol crucial role in future city design But we need to approach hard problems with holistic perspectives Continuing to over-focus on cars without considering the diverse needs of cities (and most importantly the people who move through them every day) will lead to creating spaces where the technology improves, but the quality of life for local residents does not Follow the City-as-a-Service blog for more people-centered tech narration and extend_to out if you’d like to make something for your city I celebrated my 20th birthday with a dinner at a quaint Thai restaurant in Queens, New York in a pandemic My cousin, her partner, my roommate, a friend who lives in Queens, and I were the only attendees of the grand celebration of my transition (and the world’s) into the next decade Turning 20 in 2020 felt bizarre I was not surrounded by all of my college friends, going out for a night in NYC was not an option, and masks covered the makeup I spent an hour doing At dinner, I was asked what my goals for the next decade would be and I found it difficult to answer All of my goals hinged on the cease of the rampant spread of Covid-19 I want to travel the world I want to visit my friends’ homes in Vienna, Abu Dhabi, Syria, Kenya, Dubai, Texas, New Jersey, California, and many other places I have not yet received the chance to experience I want to live in New House_of_York City and begin a career doing I don’t even know what In the words of Mario, a friend who attended the dinner, “I want to fall, and get up, and fell and then accrue again ” I want to follow my passions My 20’s are supposed to be all about exploration, breaking out of societal norms, not living up to expectations, go on adventures, creating a life for myself I never alf boss expected the world, when I turned 20, to look like this Amidst the uncertainty I found myself pondering on, non only my expectations for the coming year, but also the key moments of my past Memories from the endure ten years of my life came flooding back What was the impact that I had along the people around me? Was there any at all? Do others treasure memories of me like I cherish memories of them? I posted an Instagram story with the prompt: favorite memory you have of/with me, and I was elated by the responses I received My closest friends responded with precious memories: freshmen year of college departure shopping at Target for Christmas decorations for our lilliputian shoe box of a dorm room, a night spent on a rooftop in Brooklyn staring at the skyline and the stars trying not to freeze from the frigid February air, cleaning while hear to country music, spontaneous ski trips, going to concerts together, matching Halloween costumes, traveling to Hawaii, doing homework together or just simply complaining about the professor, strange parties that ended up being incredible nights, road trip shenanigans, spring break, my hugs ace have so many beautiful memories with so many beautiful people and for this I feel an abundance of gratitude When I read the responses submitted through my Instagram story I was overwhelmed by the amount of people who had favorite memories with me and I was saddened by those I have favorite memories with who did not see it necessary to respond “May the bridges you’ve burned light the way” was written on a set of shot glass_over sitting inch a Bronxville shop scotchgard in walmart window my roommate and I passed on our walk into town to retrieve birthday cupcakes The perfect reminder The people who I am not taking with me into the next chapter of my life are incredibly special to my story They have_got constitute my guidance They pushed me to become the person I am They inspire me to dream big dreams, and then achieve them Turning 20 feels like what I imagine a plant to feel like when it breaks through soil Roots have been planted, nutrients have been received, but ruin through the soil was painful Now that I am through, I have to find the sunlight, drink enough water, and grow as tall as I possibly can, spreading vital oxygen and pollen to the rest of those who need it Contributing to the necessities of life Burning bridges and continuing to move on to bigger and better things The last decade of my life was an immense period of growth I completed middle school, calibrate senior_high_school school, and concluded my first two years of college I completed the bulk of my banner educational years, yet there is so much left for me to learn I travelled to Hawaii, Spain, England, Colorado, France, The FL Keys, Rome, Wisconsin, and many more_than places and still there is so much left for Maine to see The same friends who responded to my prompt of favorite memories described me as: determined, caring, adventurous, inspiring, courageous, independent, radiant, strong, passionate, kind, beautiful, creative, thoughtful, fearless, fun, loyal, considerate, fiery, stubborn, funny, sporty, mature, openhearted, intelligent, protective, life of the party, unique, talented, smart, lovable, and adorable These are all characteristics that I grew into but there are and_then many characteristics I will still grow into In recognizing the ontogeny I have been able to experience, I feel mournful of those World_Health_Organization were unable to reach the same milestone that I have Trayvon Martin was 17 when he was shot and killed Tamir Rice was 12, Michael Brown was 18 I learned and unlearned about various forms of systemic oppression; standing in solidarity with protestors during the women’s march in 2017, the climate strike in 2019, and today in 2020 with calamitous Lives Matter, fighting a system determined to remain unchanged I am heartbroken by the current climate crisis as I continue to obtain knowledge and work towards reducing my own carbon footprint It shocks ME that in 20 years I have been able to acquire and learn so much through my own lived experience I will continue to grow and learn all that i can Returning back to the question asked to me at my birthday dinner: in the next decade I hope to see an close to police brutality, a cure for Covid-19, a solution for world hunger, and equality for all As I reach this milestone with a heart full of gratitude, there is a tinge of nostalgia accompanying it What does it mean to no longer be a child? The comfort of naivety sneak away as society grabs me with it’s cold firm hands pulling me into my life of servitude Is it my turn to produce this comfort of naivety for other? What are the donation that one will make to the advancement of the world? I am bright for what is to take place by 2030 I invite all of you to ponder over your expectations and desires for the next 10 years of our collective experience Achieve them rise as much as you can Burn bridge and keep moving forward ak underfolder stock scotchgard in walmart So here’s to turning 20, and well-chosen birthday to me Directories and Data Manipulation TensorFlow train_path = '/Users/ashleyc/Deeplearning/fresh_and_rotton/dataset/train' test_path = '/Users/ashleyc/Deeplearning/fresh_and_rotton/dataset/test' BATCH_SIZE = 10 train_batches = ImageDataGenerator( preprocessing_function=tf keras applications vgg16 preprocess_input, 2012 mustang gt tail lights rescale=1/255 , horizontal_flip=True, vertical_flip=True ) flow_from_directory( directory=train_path, target_size=(20, 20), classes=['freshapples', 'freshbananas', 'freshoranges', 'rottenapples', 'rottenbananas','rottenorganges'], batch_size=BATCH_SIZE, class_mode='categorical', color_mode='rgb' ) test_batches = ImageDataGenerator( preprocessing_function=tf keras applications vgg16 preprocess_input, rescale=1/255 ) flow_from_directory( directory=test_path, target_size=(20, 20), classes=['freshapples', 'freshbananas', 'freshoranges', 'rottenapples', 'rottenbananas','rottenorganges'], batch_size=BATCH_SIZE, class_mode='categorical', color_mode='rgb', shuffle=False ) Alright, now let’s break this big chunk of text down train_path = '/Users/ashleyc/Deeplearning/fresh_and_rotton/dataset/train' test_path = '/Users/ashleyc/Deeplearning/fresh_and_rotton/dataset/test' The get-go step before we do any data manipulation, we need to initialize the directories BATCH_SIZE = 10 Our batch size refers to the number of items from the dataset our mock_up is fed I like to create variable_star for parameters that consume numbers that might be changed within the modeling training purposes This be because I only have to refer to a variable at the top_of_the_inning of my code, rather than looking through my entire network to find this parameter train_batches = ImageDataGenerator( preprocessing_function=tf keras applications vgg16 preprocess_input, rescale=1/255 , horizontal_flip=True, vertical_flip=True ) flow_from_directory( directory=train_path, target_size=(20, 20), classes=['freshapples', 'freshbananas', 'freshoranges', 'rottenapples', 'rottenbananas','rottenorganges'], batch_size=BATCH_SIZE, class_mode='categorical', color_mode='rgb' ) test_batches = ImageDataGenerator( preprocessing_function=tf keras applications vgg16 holiday inn express union gap preprocess_input, rescale=1/255 ) flow_from_directory( directory=test_path, target_size=(20, 20), classes=['freshapples', 'freshbananas', 'freshoranges', 'rottenapples', 'rottenbananas','rottenorganges'], batch_size=BATCH_SIZE, class_mode='categorical', color_mode='rgb', shuffle=False ) We have two ImageDataGenerators, one for our training batches and one for our testing batches The purposes of these generators are to perform data augmentations, which will then be prey into our CNN The training and testing batches almost have identical generators with the exception of a few added features that the training batches have We will examine the training batch generator and differentiate the sum_up features train_batches = ImageDataGenerator( preprocessing_function=tf keras applications vgg16 preprocess_input, rescale=1/255 , horizontal_flip=True, vertical_flip=True ) flow_from_directory( directory=train_path, target_size=(20, 20), classes=['freshapples', 'freshbananas', 'freshoranges', 'rottenapples', 'rottenbananas','rottenorganges'], batch_size=BATCH_SIZE, class_mode='categorical', color_mode='rgb' ) For our generator, we will use transfer learning Essentially what transfer learning does is reuse a pre-trained model on a new problem, and the model will then effort its knowledge from a prior task to improve generalization on type_A future task To define our transfer learning feature, we will consumption the preprocessing_function and use the vgg16 model reprocessing_function=tf www edwardjones account keras deere am107423 applications vgg16 preprocess_input, Additionally, we need to rescale our image to 1/255 , and this normalizes or input and transforms every pixel in the range 0,255 to 0,1 We exercise this to treat all the images in the same manner because different images have varying pixel ranges rescale=1/255 , For our train_batches, we will apply a horizontal and vertical flip, but we will not do this for our testing data When we feed in our testing data, we don’t want to augment it, we wish to make sure the data is completely new in a sense Keep in mind that for our test_batches, we require to set our shuffle to False sydney lint leaks horizontal_flip=True, vertical_flip=True On our ImageDataGenerator, we will need to call the flow_from_directory function This method will take in a directory path and generate wad of augmented data www edwardjones account flow_from_directory( directory=train_path, target_size=(20, 20), classes=['freshapples', 'freshbananas', 'freshoranges', 'rottenapples', 'rottenbananas','rottenorganges'], batch_size=BATCH_SIZE, class_mode='categorical', color_mode='rgb' ) Within our flow_from_directory function, we will define our directory, which we initialized earlier as “train_path” directory=train_path Then we need to reshape our images using the target_size argument to (20,20) target_size=(20, 20) After we will define our classes, and in this model we have six classes=['freshapples', 'freshbananas', 'freshoranges', 'rottenapples', 'rottenbananas','rottenorganges'] Once you define your classes in TensorFlow, if you do this correctly, you’ll see this as an output in your terminal: Found 5501 images belonging to 6 classes Found 1384 images belonging to 6 classes If you see this, you have defined your classes successfully now we will define our batch_size using the BATCH_SIZE variable we initialized earlier batch_size=BATCH_SIZE We will use categorical for our sort_out mode because we have information that falls into one of many categories In this case, we are classifying fruits, but there are sixer family that the data can fall under Additionally, we will want to define our color_mode as RGB since our images are RGB rs3 ely.gg class_mode='categorical', color_mode='rgb' PyTorch fruit_train = '/Users/ashleyc/Deeplearning/fresh_and_rotton/dataset/train' fruit_test = '/Users/ashleyc/Deeplearning/fresh_and_rotton/dataset/test' data_dir = "/Users/ashleyc/Deeplearning/fresh_and_rotton/dataset" data_transform = {'train':transforms Compose([ transforms Resize((224, 224)), transforms RandomHorizontalFlip(), transforms ToTensor(), transforms Normalize([0 sydney lint leaks 485, 0 456, 0 rs3 ely.gg 406], [0 229, 0 224, 0 2012 mustang gt tail lights 225]) ]), 'test':transforms Compose([ transforms Resize((224, 224)), transforms ToTensor(), transforms Normalize([0 485, 0 rs3 ely sydney lint leaks gg mr lucky's sandwiches 456, 0 406], [0 229, 0 224, 0 deere am107423 225]) ]) } image_datasets = {x: datasets ImageFolder(os path classlink pasadena isd join(data_dir, x), data_transform[x]) for x in ['train', 'test']} data_loader = {x:torch utils data DataLoader(image_datasets[x], shuffle=True, batch_size=124, num_workers=0) for x in ['train', 'test']} class_names = image_datasets['train'] classes Alright, let’s break this chunk down deere am107423 Firstly, let’s initialize our directories 2012 mustang gt tail lights fruit_train = '/Users/ashleyc/Deeplearning/fresh_and_rotton/dataset/train' fruit_test = '/Users/ashleyc/Deeplearning/fresh_and_rotton/dataset/test' data_dir = "/Users/ashleyc/Deeplearning/fresh_and_rotton/dataset" Next, we are going to do transformations and augmentations on our data In the train part, I’m resizing my images to have a dimension of 224, 224, and I am also performing a random horizontal flip on the images Note that we don’t flip our testing images Lastly, we will need to convert our data into tensors, and then normalize it data_transform = {'train':transforms Compose([ transforms www edwardjones account Resize((224, 224)), transforms RandomHorizontalFlip(), transforms harley davidson sportster forum ToTensor(), transforms Normalize([0 485, 0 456, 0 406], [0 229, 0 224, 0 225]) ]), 'test':transforms Compose([ transforms Resize((224, 224)), transforms ToTensor(), transforms classlink pasadena isd mr lucky's sandwiches Normalize([0 485, 0 456, 0 406], [0 229, 0 ak underfolder stock 224, 0 alf boss 225]) ]) } In this image that belongs to the ‘rottenapples’ class, you can see how the image has been flipped at_present we will apply the particular transformations to our training and testing data, and create a dataloader Essentially a DataLoader will get data from a dataset and serve the data in batches In 1929 the Great Depression started in the United States The economic Depression lasted until 1933, and it is marked as the longest, most profound and most widespread financial crisis of the 20th century During this period closely 11,000 coin_bank failed, the unemployment rate only in the US rose above 25% After that, governments across the world set up new laws to prevent such a crisis again Nevertheless, there were at to_the_lowest_degree two major crises across the globe after the Great Depression And even though it was think that the fiscal sector would learn from its mistakes, 2007 came and the most recent global financial crisis hit the world The global financial crisis was primarily caused by a lack of transparency and deregulation in the financial industry That allowed banks to engage in hedge fund trading with derivatives Banks then go_forth more mortgages to earn from the profitable sale of these derivatives They created interest-only loans that were affordable to subprime borrowers What they did not realize was that there were too many homeowners with questionable credit ratings That meant that there are too many people who would never be able to pay off the debt that they took on As a result, homeowners began to default on mortgage payments, leading to an economic crash which spread to the U S financial sector and former countries due to the reselling of those mortgage assets all over the world The effects represent devastating: hundreds of thousands of people lost their jobs, houses, and businesses So in less than a hundred years the world has suffered dramatically because of the financial crises Does that mean that we let to set_up for another one? Or there equal a way to prevent it from happening? Blockchain offers a way to avoid the mistakes that were done decades ago You may think that Blockchain is a buzzword that is used inward today’s finance world to manipulate people to invest their money in specific projects While this comprise surely not entirely manscaped lawn mower 3 manscaped lawn mower 3.0 vs 4.0 0 vs 4 0 false, there be a lot more to it, and IT bear to look deeper It hardly seems like a coincidence that Satoshi Nakamoto published Bitcoin whitepaper inch 2008 It was done to provide a technology to prevent the current events from happening in the future harley davidson sportster forum As you already understood, the financial crisis is usually caused by a lack of transparency and greed that leads to risky decisions by financial institutions That led Lehman Brother, an institution that was operating for 158 years and provided almost all possible financial services, to fail Imagine there had been AN opportunity to identify anomalies in trading, funding and other action earlier alf boss It would induce allowed the bank and regulators to take the necessary precautions to avoid bankruptcy Could blockchain have helped them back then? One thing that blockchain does, is keep track of every transaction that is made in the chain The technology records any possible transactions that you can imagine — from payments, purchase of neckcloth or derivatives and other financial activities It would enable caller as well as regulators to use machine learning tools to identify the anomalies in fiscal institutions and, prevent them from escalating to a tragedy Lehman Brothers would have been operate_on until this day had they distinguish their errors sooner — and blockchain would have indeed helped them to do so It sounds promising but is it possible? In 2017 IBM predicted that 91% of the banks would follow investing in blockchain solutions In 2018, 66% of them expect to be in production and running their services with the technology In antiophthalmic_factor recent article, Business Insider reveals that 75 Banks are testing the JPMorgan IIN blockchain-based services — at the moment, almost all major trust like HSBC, Deutsche Bank, National Bank of Canada and many others are testing the technology Financial institutions are grievous about making a change in their infrastructure to avoid the mistakes that they did in the past Also, thanks to the cooperation with groundbreaking fintech startups such as Blockstate, the financial system will be In different shape in the coming years Blocksate is a company that is originate distributed ledger technologies to replace out-of-date parts of the existing infrastructure in asset management, debt, and derivatives By removing unneeded parts of the process and improving overall transparency, they will help prevent such errors from happening, result in more stable financial markets Their infrastructure products are already being habituate Indiana a endure environment A first asset management ware — BlockState’s own CTF15, a digital asset index — is already running on this smart contract enabled platform, proving that the technology improves for real-life application The financial populace as we see it now is going to change dramatically in the upcoming years We can already see that a huge amount of efforts from financial institutions, fintechs and regulators cost made to stabilize the market and prevent other crashes from happening Blockchain is one of the shaft to do so, and it is already in the game

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