Share via Shortlink Message* Tags “At a time when people are struggling to put food on the table, it is crucial that affordable grocery options remain available,” Rosenthal wrote in her letter to Brodsky.Brooklyn Fare is renovating the space and expects to open the store this summer.“Lincoln Square is a great neighborhood for our expansion of the Brooklyn Fare brand, and the concept caters to shoppers at all price points which the area needs,” said Moe Issa, the owner of Brooklyn Fare. “We sell everyday items up to high-end niche cooking-related products. We are very confident Brooklyn Fare will be embraced.”Lee & Associates’ Brad Schwarz worked on the deal along with JP Sutro and Morris Dweck.Lincoln Square is in the midst of a major transformation, including the opening of GID Development Group’s Waterline Square luxury condo complex last year.Contact Akiko Matsuda Share on FacebookShare on TwitterShare on LinkedinShare via Email Share via Shortlink Full Name* Email Address* 75 West End Avenue (Photos via Brodsky, Wikipedia Commons)Brooklyn Fare is expanding its footprint into the Upper West Side.The grocer has signed a 25-year, 21,600-square-foot lease at the base of the Brodsky Organization’s rental building at 75 West End Avenue, within the Lincoln Square submarket. The asking rent for the space was $85 per square foot, according to Lee & Associates NYC, which brokered the deal.This is the fourth New York City location for Brooklyn Fare, which has existing stores in Hell’s Kitchen, the West Village and Downtown Brooklyn.Until recently, the space was occupied by a Western Beef supermarket. In response to the news of the grocer’s impending closing, Assemblymember Linda Rosenthal, who represents the area, asked the landlord in December to consider the needs of her constituents, including residents of NYCHA’s nearby Amsterdam Houses, West Side Rag reported.Read more“Safer than a bank”: South American family scoops up 8 units at GID’s Waterline SquareThese grocery stores saw the biggest drops in foot trafficOutdoor space seals deal in tough luxury market Brodsky OrganizationCommercial Real EstateRetail Real Estate
By Jon ZacksThe Huskies were missing players and brains on Monday night, as they dropped game one of their second-round playoff series to the Grande Prairie Wheelers. The second-ranked Huskies were almost doubled in shots (47-25) and pressured for long stretches in their own zone, for almost the entire 60 minutes.- Advertisement -Missing a legion of key players, the pups played short-benched and with three Midget call-ups on defence. With Payden Wongstedt, Jesse Disher, and Kyle Porter all suspended, the Fort St. John squad was also missing Dylan Apsassin, Ryan Stickel, Cash Brinkworth, Cam MacKinnon, and Brighton Campbell, and the absence were glaring. “Huge” was how Huskies Assistant Coach Jeremy Clothier described the missing bodies. “You show up to a hockey game, and a couple of your guys aren’t here … they just don’t show up” he lamented. “It hurts the dressing room a little bit.”The Wheelers took full advantage, sending a relentless forecheck deep into the FSJ zone, and creating endless scoring chances. By the end of the first period, Grande Prairie was up 3-0, and while the Huskies took advantage of some powerplays in the second to climb back into the game, the Wheelers soon pulled away again.Grande Prairie got offensive contributions from almost the entire lineup, with Kyle Weegar and Cordell Shmyr both scoring a pair of goals, and Riley Halwa, Nathan Johnson and Jarvis Dawson also finding the back of the net. “They got shots” said Clothier of Grande Prairie’s success. “They drove the net, they stayed out of the penalty box, they out forechecked us, and they outworked us.”Advertisement Kole Norris led the way offensively for Fort St. John, recording two goals and an assist, while Robbie Sidhu also had a pair of goals. Ty Gullickson got his fourth consecutive start, and actually played remarkably well, despite conceding 8 goals. Kris Dika won his fourth game of the playoffs, after playing each game in Grande Prairie’s first-round sweep of Sexsmith. Cody Poggenpohl was one of the three NEBC and Yukon Tracker-Flyers to dress for the Huskies on the back-end. “I’m still little out of shape” he admitted afterwards, referring to a torn ligament that has kept him off the ice, adding “I think it was a lot of fun out there.” It was Poggenpohl’s first game with the Huskies, while his Midget teammates David Green and Jordan Walters had both played in the 2009 playoffs. Poggenpohl had his own theory on what led to the Huskies demise on Monday, suggesting simply “we couldn’t get the puck out.” The Huskies coaching staff seemed pleased with the performances of all three Midgets, giving all of them plenty of ice time in all situations. “They fit in good” said Jeremy Clothier, adding “they work hard, they’re physical, they know what they have to do out there.”Advertisement The final score was 8-4 in favour of the guests, with the series now shifting back to Grande Prairie for game two on Wednesday night. “We’ve got to get better game-preparation” advised Cody Poggenpohl, who is expecting to dress on Wednesday. “We walked into this game and no one was really into it … so next game we’ve just got to get into it more.”
A group of unprivileged women in Hout Bay use tea bags as a main resource to design products to support their families. (Image: YouTube)What started out as an initiative to empower unprivileged women in Hout Bay is now a business that supports families and reaches as far as Europe.Original T-Bag Designs was born out of a desire to help some women from ImizamoYethu, an informal settlement in Hout Bay, Cape Town, earn money. It is now a registered company, the crafters are employeesof this company and the sale of their crafts pays their monthly salaries. And interestingly, those products are made out of recycled tea bags.They include gift cards, trays, coasters, bags, dolls, notebooks, and boxes. “With recycled tea bags as their canvases they are painting themselves out of poverty,” the company says of its artists.The items are sold locally as well as in Germany, where a supporter has been been ordering from the company for years. In February, the company was approached by a French designer, who asked Original T-Bag Designs to collaborate and and remake two of its products to sell in Paris.“The young French designer saw a bag that is made by one of T-Bag Designs’ staff, Gracious Dube,” says Helen White the operations manager. “She wanted to collaborate with Gracious to modify her bag and one of our products so that she could sell them in her shop, Ithemba Design Ethik in Paris.” These coasters are of the products designed by several artists who make use of tea bags as their canvas. (Image: Original T-Bag Designs)IN THE BEGINNINGJill Heyes, a former art teacher, moved from England to South Africa in 1996. Seeing the poverty in Imizamo Yethu, in the seaside suburb of Hout Bay, she decided to do something to help the underprivileged women.White says Heyes started in 2000 by teaching basic craft skills to a few women. She felt that the products she came up with were not special enough for people to want to buy them. A special friend of hers made the suggestion of using a tea bag and it was decided that this would be a canvas for the ladies to express their creativity on. The tea bags were then put on cards and stationary items.The company has been in full swing since 2003. “We grew from about seven when the company was registered in 2003 to currently having 18 staff members,” explains White, who has been working at T-Bag Designs for the past 10 years. We also have two full time managers and two part-timeoffice support staff.”Heyes wanted to make sure that Original T-Bag Designs was sustainable. White explains: “We do not need to ask for or rely upon donations as we have put profits from our sales back into the company as we have grown over the years.” Russell Chitanda, production manager, and Jill Heyes, founding member, are part of the team that ensures that the average of 3 000 tea bags are painted for a week. (Image: Original T-Bag Designs)THE WORKLOADMost of the artists paint 150 to 250 tea bags a week, depending on how the sales go, she says. “On average we would get through about 3 000 [tea bags] a week just for painting. We also use them for our Heart range. These are only painted one colour then a heart is cut out of the tea bag. This would bring the total up to about 4 000 a week,” White says.Donations of used tea bags are a continuous request. People are asked to dry the bags, remove the tea leaves and send the paper to Original T-Bag Designs, where each artist creates her own designs.For more information, go to Original T-Bag Designs.
Parked vehicle, four businesses shot at with BB gun in College Area Broken Glass Everywhere!!! Several Businesses Are Vandalized By Punks In College Area Of San Diego. Windows Shot Out By B.B. Gun? Reaction Tonight On KUSI pic.twitter.com/BjCq7porQv— Dan Plante (@DanPlanteKUSI) July 8, 2019 00:00 00:00 spaceplay / pause qunload | stop ffullscreenshift + ←→slower / faster ↑↓volume mmute ←→seek . seek to previous 12… 6 seek to 10%, 20% … 60% XColor SettingsAaAaAaAaTextBackgroundOpacity SettingsTextOpaqueSemi-TransparentBackgroundSemi-TransparentOpaqueTransparentFont SettingsSize||TypeSerif MonospaceSerifSans Serif MonospaceSans SerifCasualCursiveSmallCapsResetSave SettingsSAN DIEGO (KUSI) – A BB gun was used to shoot out windows at four businesses in the College Area along with a side window of a vehicle parked nearby, police said Monday.The damage was reported around 9:35 p.m. Sunday in the 7100 block of El Cajon Boulevard, San Diego police public-affairs Officer Billy Hernandez said.Officers arrived and found windows shattered at four businesses in the area as well as the driver’s side rear window of a parked vehicle, Hernandez said.No injuries were reported and no suspect descriptions were immediately available. Updated: 5:19 PM Categories: Local San Diego News FacebookTwitter Posted: July 8, 2019 KUSI Newsroom, KUSI Newsroom July 8, 2019
Darjeeling: In a move set to benefit the Gorkha community significantly, Chief Minister Mamata Banerjee on Wednesday laid the foundation stone for a Gorkha Welfare Centre in Delhi.Banerjee, who was in Delhi on Wednesday to attend the AAP rally, laid the foundation stone for the centre, which will come up at Saket in Delhi. “The centre will be a big help for the students and patients visiting Delhi from the Hills. This is a permanent asset for Darjeeling. It is being done jointly by the state government and the GTA,” stated the Chief Also Read – Bose & Gandhi: More similar than apart, says Sugata BoseMinister in her address. A four-storied building will come up in the 28,820 sq feet area at a cost of Rs 20 crore. “This land was given to the DGHC 18 years ago. However, the DGHC and the GTA had failed to come up with anything concrete here. Later, when we took charge of the GTA, we approached the Chief Minister with a proposal for the welfare centre. She immediately agreed. The land had been encroached by land mafia. We had to seek legal recourse with the help of the state government to get back the land,” stated GTA chairman Binay Tamang. Also Read – Rs 13,000 crore investment to provide 2 lakh jobs: MamataThe aim of the centre is to provide accommodation to students who come to Delhi to appear for different examinations, interviews and for patients who come for treatment. It will also serve as a guest house for officials travelling to Delhi. 85 percent of the land will be used for residential purpose, while the rest will be institutional. “The centre is not just for Gorkhas but for all communities. It is not just for the Darjeeling and Kalimpong Hills but for Gorkhas residing throughout India,” added Tamang.
Hear from business owners and CEOs who went through a crippling business problem and came out the other side bigger and stronger. Problem Solvers with Jason Feifer 2 min read October 16, 2014 Initially announced in June, OS X Yosemite — Apple’s new operating system for Macs — is available today as a free upgrade, alongside a brand new iMac to showcase the revamped interface in all its glory.While Apple’s uber-sharp Retina display made its debut on the iPhone 4 in 2010 and subsequently arrived on the third generation iPads and Macbook Pros in 2012, the company is now bringing its high-resolution display to desktops.A new iMac will feature a 27-inch Retina 5K display, Apple said, that is jam-packed with 14.7 million pixels — more than four times the pixels in a standard 27-inch iMac display.Related: Apple’s Latest iPads Are Thinner, Faster and Equipped With Touch IDThis is all the better to experience the new Yosemite operating system, Apple said, which touts a new feature called “continuity” that enables users to make phone calls and send text messages directly from their desktops.The new iMac, which marks the first update to the range since 2011, will ship today, priced at $2,499. A normal 27-inch iMac, by comparison, starts at $1,799.And at an event earlier today in Cupertino, Calif., Apple also took the opportunity to update its somewhat lesser-known Mini Mac — a 7.7-inch computer to which users must connect their own display, keyboard and mouse. Last updated in 2012, the new Mini Macs are equipped with new processors and are priced at $499 — $100 less than their previous price. They also ship today.Related: Apple Pay Officially Arrives Monday, Oct. 20 Listen Now
April 10, 2017 3 min read Register Now » Growing a business sometimes requires thinking outside the box. Free Webinar | Sept. 9: The Entrepreneur’s Playbook for Going Global This story originally appeared on Engadget Uber has finally responded via the courts to Waymo’s allegation that it’s using the Alphabet company’s Lidar technology. The ride-hailing company called Waymo’s injunction motion to stop using technology that was allegedly misappropriated from Google servers a “misfire.” It also insisted that because it’s developing multi-lens LiDAR technology instead of the single-lens that Waymo uses, it’s not using stolen technology.Waymo’s lawsuit against Uber claims that former Google engineer, Anthony Levandowski stole 14,000 confidential documents pertaining to the search giant’s LiDAR tech and that Uber is using the technology found in those documents.After he left Google Levandowski went on to form the self-driving trucking company Otto that was acquired by Uber for $680 million. He currently leads Uber’s driverless car initiative.In the response to the injunction, Uber was forced to note that Waymo’s self-driving technology is currently ahead of the ride-hailing company’s. That’s not too surprising considering that Google started working on its self-driving tech in 2009, five years ahead of Uber. Uber also admitted that it’s still using off-the-shelf technology from LiDAR supplier Velodyne.Still Uber notes that it’s upcoming proprietary LiDAR is vastly different from Waymo’s.”Waymo’s injunction motion is a misfire: there is no evidence that any of the 14,000 files in question ever touched Uber’s servers and Waymo’s assertion that our multi-lens LiDAR is the same as their single-lens LiDAR is clearly false,” said Angela Padilla, Uber associate general counsel said in a statement. “If Waymo genuinely thought that Uber was using its secrets, it would not have waited more than five months to seek an injunction. Waymo doesn’t meet the high bar for an injunction, which would stifle independent innovation and competition.”The Alphabet company brought the lawsuit in response to an Uber email that was accidentally CC’d by a LiDAR component vendor to one of Google’s employees that contained an Uber circuit board that allegedly resembled Waymo’s proprietary design.In its response Uber states: “Waymo took one Uber schematic (inadvertently sent to a Waymo employee) and made several assumptions based on that one document to conclude that Uber’s LiDAR used a single-lens design”A Waymo spokesperson told Engadget: “Uber’s assertion that they’ve never touched the 14,000 stolen files is disingenuous at best, given their refusal to look in the most obvious place: the computers and devices owned by the head of their self-driving program. We’re asking the court to step in based on clear evidence that Uber is using, or plans to use, our trade secrets to develop their LiDAR technology, as seen in both circuit board blueprints and filings in the State of Nevada.”This trial could be spell trouble for Uber. If it’s found that one of its top executives did pilfer those documents and use the information within them to build Uber’s LiDAR technology, the financial judgement could cripple the ride-hailing company and give competitors like Lyft the opportunity to overtake it.
As a category manager, I manage the data science portfolio of product ideas for Packt Publishing, a leading tech publisher. In simple terms, I place informed bets on where to invest, what topics to publish on etc. While I have a decent idea of where the industry is heading and what data professionals are looking forward to learn and why etc, it is high time I walked in their shoes for a couple of reasons. Basically, I want to understand the reason behind Data Science being the ‘Sexiest job of the 21st century’, and if the role is really worth all the fame and fortune. In the process, I also wanted to explore the underlying difficulties, challenges and obstacles that every data scientist has had to endure at some point in his/her journey, or still does, maybe. The cherry on top, is that I get to use the skills I develop, to supercharge my success in my current role that is primarily insight-driven. This is the first of a series of posts on how I got started with Data Science. Today, I’m sharing my experience with devising a learning path and then gathering appropriate learning resources. Devising a learning path To understand the concepts of data science, I had to research a lot. There are tons and tons of resources out there, many of which are very good. Once you seperate the good from the rest, it can be quite intimidating to pick the options that suit you the best. Some of the primary questions that clouded my mind were: What should be my programming language of choice? R or Python? Or something else? What tools and frameworks do I need to learn? What about the statistics and mathematical aspects of machine learning? How essential are they? Two videos really helped me find the answers to the questions above: If you don’t want to spend a lot of your time mastering the art of data science, there’s a beautiful video on how to become a data scientist in six months What are the questions asked in a data science interview? What are the in-demand skills that you need to master in order to get a data science job? This video on 5 Tips For Getting a Data Science Job really is helpful. After a lot of research that included reading countless articles and blogs and discussions with experts, here is my learning plan: Learn Python Per the recently conducted Stack Overflow Developer Survey 2018, Python stood out as the most-wanted programming language, meaning the developers who do not use it yet want to learn it the most. As one of the most widely used general-purpose programming languages, Python finds large applications when it comes to data science. Naturally, you get attracted to the best option available, and Python was the one for me. The major reasons why I chose to learn Python over the other programming languages: Very easy to learn: Python is one of the easiest programming languages to learn. Not only is the syntax clean and easy to understand, even the most complex of data science tasks can be done in a few lines of Python code. Efficient libraries for Data Science: Python has a vast array of libraries suited for various data science tasks, from scraping data to visualizing and manipulating it. NumPy, SciPy, pandas, matplotlib, Seaborn are some of the libraries worth mentioning here. Python has terrific libraries for machine learning: Learning a framework or a library which makes machine learning easier to perform is very important. Python has libraries such as scikit-learn and Tensorflow that makes machine learning easier and a fun-to-do activity. To make the most of these libraries, it is important to understand the fundamentals of Python. My colleague and good friend Aaron has put out a list of top 7 Python programming books which helped as a brilliant starting point to understand the different resources out there to learn Python. The one book that stood out for me was Learn Python Programming – Second Edition – This is a very good book to start Python programming from scratch. There is also a neat skill-map present on Mapt, where you can progressively build up your knowledge of Python – right from the absolute basics to the most complex concepts. Another handy resource to learn the A-Z of Python is Complete Python Masterclass. This is a slightly long course, but it will take you from the absolute fundamentals to the most advanced aspects of Python programming. Task Status: Ongoing Learn the fundamentals of data manipulation After learning the fundamentals of Python programming, the plan is to head straight to the Python-based libraries for data manipulation, analysis and visualization. Some of the major ones are what we already discussed above, and the plan to learn them is in the following order: NumPy – Used primarily for numerical computing pandas – One of the most popular Python packages for data manipulation and analysis matplotlib – The go-to Python library for data visualization, rivaling the likes of R’s ggplot2 Seaborn – A data visualization library that runs on top of matplotlib used for creating visually appealing charts, plots and histograms Some very good resources to learn about all these libraries: Python Data Analysis Python for Data Science and Machine Learning – This is a very good course with a detailed coverage on the machine learning concepts. Something to learn later. The aim is to learn these libraries upto a fairly intermediate level, and be able to manipulate, analyze and visualize any kind of data, including missing, unstructured data and time-series data. Understand the fundamentals of statistics, linear algebra and probability In order to take a step further and enter into the foray of machine learning, the general consensus is to first understand the maths and statistics behind the concepts of machine learning. Implementing them in Python is relatively easier once you get the math right, and that is what I plan to do. I shortlisted some very good resources for this as well: Statistics for Machine Learning Stanford University – Machine Learning Course at Coursera Task Status: Ongoing Learn Machine Learning (Sounds odd I know) After understanding the math behind machine learning, the next step is to learn how to perform predictive modeling using popular machine learning algorithms such as linear regression, logistic regression, clustering, and more. Using real-world datasets, the plan is to learn the art of building state-of-the-art machine learning models using Python’s very own scikit-learn library, as well as the popular Tensorflow package. To learn how to do this, the courses I mentioned above should come in handy: Stanford University – Machine Learning Course at Coursera Python for Data Science and Machine Learning Python Machine Learning, Second Edition Task Status: To be started During the course of this journey, websites like Stack Overflow and Stack Exchange will be my best friends, along with the popular resources such as YouTube. As I start this journey, I plan to share my experiences and knowledge with you all. Do you think the learning path looks good? Is there anything else that I should include in my learning path? I would really love to hear your comments, suggestions and experiences. Stay tuned for the next post where I seek answers to questions such as ‘How much of Python should I learn in order to be comfortable with Data Science?’, ‘How much time should I devote per day or week to learn the concepts in Data Science?’ and much more.. Read more Why is data science important? 9 Data Science Myths Debunked 30 common data science terms explained