Star Trek S1E02 "Who Mourns for Adonais?" #TOS #StarTrek https://t.co/LIkzMGcPIi has interesting features 1) sexism tempered by female crew members' competence, (2) advancement of Ancient Aliens theory & 3) use of Pre-Modern anti-Muslim slur 4) appearance of Walter Koenig: Chekov

Remembering the Bengali scientist Dr Subhash Mukhopadhyay- the Pioneer of IVF in India, the creator of India's first and world's second child using IVF on his birth anniversary. The Father of IVF in India who was rewarded with suicide was born on 16.01.1931in Hazaribagh.
#Thread

Dr. Subhash was the son of a doctor and studied at the National Medical College in Kolkata after completing his schooling. Fascinated by innovations in gynaecological surgery from his early days as a medical student, he completed his PhD in reproductive physiology +

from the University of Calcutta before going to the Edinburgh University in UK for a PhD in reproductive endocrinology. On his return to India in 1978, he started researching ovulation and spermatogenesis. Soon after, he teamed up with Sunit Mukherji, a cryobiologist +

and Saroj Kanti Bhattacharya, a gynaecologist, to work on a method of in-vitro fertilization for a patient (Bela Agarwal) with damaged fallopian tubes. +

Mukhopadhyay with a double PhDstarted work on IVF techniques in the mid 60s and created history by becoming the first physician in India and second in the world after British physicians Robert Edwards and Patrick Steptoe) to perform the In-vitro fertilisation. +

Important paper from Google on large batch optimization. They do impressively careful experiments measuring # iterations needed to achieve target validation error at various batch sizes. The main "surprise" is the lack of surprises. [thread]

https://t.co/7QIx5CFdfJ

The paper is a good example of lots of elements of good experimental design. They validate their metric by showing lots of variants give consistent results. They tune hyperparamters separately for each condition, check that optimum isn't at the endpoints, and measure sensitivity.

They have separate experiments where the hold fixed # iterations and # epochs, which (as they explain) measure very different things. They avoid confounds, such as batch norm's artificial dependence between batch size and regularization strength.

When the experiments are done carefully enough, the results are remarkably consistent between different datasets and architectures. Qualitatively, MNIST behaves just like ImageNet.

Importantly, they don't find any evidence for a "sharp/flat optima" effect whereby better optimization leads to worse final results. They have a good discussion of experimental artifacts/confounds in past papers where such effects were reported.

5 star RSI Strategy by @VishalMalkan

Unconventional approach of 60-40 RSI and range shift concept.

According to him,
whenever the market is bearish,
it won’t be able to cross 60,
and whenever in a bullish trend,
it won’t be able to cross 40.

Like & Retweet for Maximum Reach.

So, instead of the 70-30 Relative Strength Index,
we will use the 60-40 range for the RSI indicator for this strategy.

When the
Monthly and Weekly RSI>60,
& when the RSI takes support at 40 in the daily chart,
it may bounce back and most probably it will not go below 40.

If a bullish candle is formed at the 40 RSI level,
the prices may bounce back, and one can enter the stock.

The stoploss can be placed at the low of that bullish candlestick,
and the target can be the 60 RSI level.

When the
Monthly and Weekly RSI<40,
& when the RSI takes resistance at 60 in the daily chart,
it may bounce back and most probably it will not go above 60

If a bearish candle is formed at the 60 RSI level,
the prices may bounce back from there, & 1 can enter the stock 4 shorting

The stoploss can be placed at the high of that bearish candlestick, and the target can be the 40 RSI levels.

#banknifty

This range shift concept can be applied in any timeframe,
whether intraday, daily,weekly, etc.