Bula Choudhury powers her way to a string of medals: Sensational debutWhen her frail, waif-like figure joined the line-up for the start of her first race, the 200 m butterfly, the general reaction bordered on sympathy. Her 34 kg weight contained in a 138 cm frame, Bula Choudhury, the 12-year-old,Bula Choudhury powers her way to a string of medals: Sensational debutWhen her frail, waif-like figure joined the line-up for the start of her first race, the 200 m butterfly, the general reaction bordered on sympathy. Her 34 kg weight contained in a 138 cm frame, Bula Choudhury, the 12-year-old entrant from West Bengal was dwarfed both literally and figuratively by her better-known and more experienced rivals.The sympathy, however, soon changed to grudging admiration, incredulity and, finally, elation as the tiny figure powered its way to a sensational record-shattering win in the event, lopping off as much as 9.6 seconds from the existing mark. No individual performer in the meet could better an existing mark by a wider margin.The general belief that Choudhury’s effort was a flash in the pool was soon dispelled as she followed up her first day’s performance with a string of medal-winning performances. On the second day of the six-day meet she added a silver medal in the 100m backstroke followed by a silver in the 800m freestyle, a bronze in the 200m medley, two more silvers in the 100m and 200m freestyle, a gold in the 100m butterfly and another silver in the 400m freestyle.Her final tally of eight medals and 43 points, five points more than closest rival Persis Madan, won her the best swimmer of the meet title and a place in Indian sporting history. Her sensational debut in the nationals, at the age of 12, is an all-time record in itself and guaranteed her a place in the relay quartet for the Brisbane Commonwealth Games as well as a prominent place on the list of Asiad probables. Says current coach Bernad Johnke: “Bula is far superior to the other 14 girls in my camp and easily the best potential in the country. She is at an early age when her body is not yet fully formed and so she can adapt better to techniques that will help improve her timings.”advertisementSelf-trained: Obviously, in that tiny frame, is a budding powerhouse, a bundle of talent, grit and going-for-gold determination. Incredibly enough, Choudhury is largely self-trained. The third of four children born to a petty trader (a wholesale dealer in combs), Bula took to water like the proverbial duck. At age six, she plunged into a local pond which became her future training ground and only graduated to the Ganges river nearby when she outgrew the pond.”Even now, she goes as often as possible to the river to swim,” says her proud mother, Bakul, who chaperons her on her various aquatic appearances. Bula’s potential and her young age make her the most exciting swimming prospect the country has had in decades. Now that she has joined the Asiad training camps and Johnke has taken her under his wing, she has the potential to develop into a champion, if not in the coming Asiad then in the next one in 1986 when she will be 16.Though not overawed by the adulation and her triumphs last fortnight, Bula still displays a childish naivety and a schoolgirlish air. That is hardly surprising considering she is still in the eighth standard at the Rajmohan Paul Balika Vidyalaya in Calcutta. When a sudden attack of fever sent her into hospital at the end of the Trial Games, and tragically aborted her hopes of accompanying the Indian team to Brisbane, she displayed more worry about what her school friends would say than disappointment at not being able to go. “I promised them I would make it to Brisbane and now how can I face them?” she wailed.Her talent, however, has earned her a Rs 900 Central Government scholarship which pays for her schooling and her training. What she has clearly lacked so far is a balanced and proper diet and expert guidance. Now that she has the benefit of both, Bula Choudhury seems all set to become a female Mark Spitz.
Philippine Arena Interchange inaugurated Hontiveros presses for security audit of national power grid The Revellers opened up with a 10-0 spurt that eventually set the tone for the humbling the Titans would experience throughout the match.Stephen Siruma led Che’Lu with 13 points and five assists while JayR Taganas added a double-double of 12 points, 10 rebounds, with five assists.FEATURED STORIESSPORTSPrivate companies step in to help SEA Games hostingSPORTSPalace wants Cayetano’s PHISGOC Foundation probed over corruption chargesSPORTSSingapore latest to raise issue on SEA Games food, logisticsChe’Lu improved to a 5-3 record in the Aspirants Group while also eliminating the Titans who dropped to a 2-5 card after the loss.“This is what I want from my team, to become a fighting one,” said Revellers head coach Stevenson Tiu in Filipino. “We may not be as experienced like last season but we still need our players to play their role.” Cayetano: Senate, Drilon to be blamed for SEA Games mess Rey Suerte, Mark Bringas, and Jhaps Bautista all had 11 points apiece to round out the double-digit scorers for Che’Lu.Joshua Munzon had 26 points for the Titans.Sports Related Videospowered by AdSparcRead Next LATEST STORIES View comments PH underwater hockey team aims to make waves in SEA Games PLAY LIST 02:42PH underwater hockey team aims to make waves in SEA Games01:44Philippines marks anniversary of massacre with calls for justice01:19Fire erupts in Barangay Tatalon in Quezon City01:07Trump talks impeachment while meeting NCAA athletes02:49World-class track facilities installed at NCC for SEA Games02:11Trump awards medals to Jon Voight, Alison Krauss DA eyes importing ‘galunggong’ anew SEA Games hosting troubles anger Duterte MOST READ Don’t miss out on the latest news and information. Sepp Blatter plans to sue FIFA, Gianni Infantino for damaging his reputation MANILA, Philippines—Che’Lu Bar and Grill dismantled AMA Online Education, 115-77, to maintain its place in the playoff race of the 2019 PBA D-League Thursday at Ynares Sports Arena in Pasig.ADVERTISEMENT Panelo: Duterte ‘angry’ with SEA Games hosting hassles Ethel Booba twits Mocha over 2 toilets in one cubicle at SEA Games venue Private companies step in to help SEA Games hosting
ICICI Securities IPO eyes Rs 4000 crore: Key points to know REUTERS/Adnan AbidiICICI Securities, the broking subsidiary of private-sector lender ICICI Bank, will hit the initial public offer (IPO) market next Thursday.The company will offer 7,72,49,508 equity shares for subscription. Here are the key things to know about the ICICI Securities IPO:• ICICI Bank proposes to raise Rs 4,020 crore by selling a 24 percent share in ICICI Securities• ICICI Securities IPO will open March 22 and close March 26. The offer will be open for anchor investors March 21• The price band of the IPO has been set at Rs 519-520 per share. Investors can apply for a minimum of 28 equity shares and multiples of 28 thereafter• Citigroup, CLSA, Edelweiss, IIFL, Bank of America Merrill Lynch, and SBI Capital Markets are the managers of the IPO• The proceeds from the issue will be headed to the bank and the equity shares offered by the company are proposed to be listed on Bombay Stock Exchange (BSE) and National Stock Exchange (NSE)ICICI Securities is the brokerage and merchant banking arm of ICICI Bank. The firm provides services including brokerage, financial product distribution, and investment banking to both institutional and retail clients.ICICI Securities got the approval from market regulator Securities and Exchange Board of India (SEBI) in February this year to float IPO.ICICI Securities is the third entity of ICICI Bank where the lender is diluting its stakes. In 2017, ICICI Bank had diluted part of its holdings in ICICI Prudential Life Insurance Company and general insurance wing — ICICI Lombard. ICICI Lombard was the first general insurer to go public.Bankers and stock market experts have predicted that 2018, like 2017, will be a busy year for capital markets. Companies from different sectors are lined up to raise crores through share-sale offers in the coming months.
Listen at WEAA Live Stream: http://amber.streamguys.com.4020/live.m3uA review of some of the top news stories of the week from the pages of the AFRO with managing editor Kamau High. Plus, our recurring guests Taya Graham and Stephen Janis (The Mod Squad) of The Real News Network, report on Baltimore politics and law enforcement.These stories and more coming up this evening on AFRO’s First Edition with Sean Yoes.
MLflow 0.8.0 released with improved UI experience and better support for deployment Last week, the team at Databricks released MLflow 0.8.0. MLflow, an open source platform used for managing end-to-end machine learning lifecycle. It is used for tracking experiments and managing and deploying models from a variety of ML libraries. It is also responsible for packaging ML code in a reusable and reproducible form in order to share the same with other data scientists. MLflow 0.8.0 features In MLflow 0.8.0, the SageMaker and pyfunc server support the ‘split’ JSON format, which helps the client to specify the order of columns. With MLflow 0.8.0, the server can now pass the gunicorn option. This is because as gunicorn uses threads instead of processes and saves memory space. This version also brings in TensorFlow 1.12 support. With this version, there’s no need of loading Keras module at predict time. Major change In MLflow 0.8.0 version, [CLI] mlflow sklearn server has been removed in favor of mlflow pyfunc serve, as it takes the same arguments but works against any pyfunc model. Major improvements in MLflow 0.8.0 This version includes various new features including improved UI experience and support for deploying models directly to the Azure Machine Learning Service Workspace. Improved MLflow UI Experience In this version, the metrics and parameters are by default grouped together in a single tabular column in order to avoid an explosion of columns. The users can customize their view by sorting the parameters and metrics. They can click on each parameter or metric in order to view them in a separate column. This makes the user experience better. The runs which are nested inside other runs can now be grouped by their parent-run. They can also be expanded or collapsed altogether. By calling mlflow.start_run or mlflow.run, a run can be nested. Though MLflow gives each run a UUID by default, one can also now assign a name to a run and also can edit the names. It makes the process easy as it is easier to remember the name than a number. There’s no need to reconfigure the view each time one uses it, as the MLflow UI remembers the filters, sorting and column setup done in browser local storage. Support for Deployment of models to Azure ML Service In this version, the Microsoft Azure Machine Learning deployment tool has been modified for deploying MLflow models packaged as Docker containers. One can use the mlflow.azureml module to package a python_function model into an Azure ML container image. Further, this image can be deployed to the Azure Kubernetes Service (AKS) and the Azure Container Instances (ACI) platforms. Major bug fixes The server works better in this version even when the environment and run files are corrupted. The Azure Blob Storage artifact repo now supports Windows paths. In the previous version, deleting the default experiment caused recreation of the same. But with MLflow 0.8.0 this problem has been fixed. Read more about this news on Databricks’ blog. Read Next Introducing EuclidesDB, a multi-model machine learning feature database Google releases Magenta studio beta, an open source python machine learning library for music artists Technical and hidden debts in machine learning – Google engineers’ give their perspective