The only data science podcast that educated me and didnât put me to sleep. It feels like Iâm sitting in on a conversation. Not sure why people are so bothered by the speakers use of filler words. This podcast is not a lecture if youâre looking for a lecture take one of Rogers classes, this podcast to me at least serves as an entertaining educational conversation. I have been exposed to plenty of new ideas and more importantly see how data scientists like Hilary and Roger think through things. So like whatâs wrong with that? Thanks Hilary and Roger!
F***ing obnoxious. Episode 1 needs to be transcribed and analyzed to see just how many times they say âlike.â Id be enjoying this if it werenât for this. Get those thoughts out coherently please.
So bummed. Took online courses from Dr. Peng and like his joyful attitude but I just cannot take all the "like, then you kind of, like, need to, like..." Some sentences contain the word "like" more than five times. I've been hunting for a good podcast on data science and the content seems really right. But quality presenters do not confound their message with with such an incredible frequency of filler words. It's also easy to fix. Join Toastmasters for a month and this will go away. meanwhile I keep looking for a good podcast on data science.
Iâve been working my way through a MS in Data Analytics so I had been looking for additional ways to keep tabs on the industry. Tune in for practical tips on what data science is in industry and academia. Try not to mind the lack of audio finishing, intro, or outro music.
I wanted to like this SO badly but I could get not get through the first episode! The woman says âlikeâ average 76 times per sentence (actual data analysis). Itâs like, way too, like, frustrating, like...
There are generally about 10-15 minutes of great discussion in each episode, but the rest of it I could do without. I find the banter annoying and I agree that there are too many filler words. That's fine for informal discussions, but if Roger and Hilary listened to each ep after recording, I think it would greatly improve their speaking. Would probably be even better if they added a 3rd and/or 4th host.
Seriously, it's like there's a laugh track playing. There's nothing funny being said, neither host is funny, but after every single comment they giggle as if there's some inside joke. It's so annoying and distracting. Stop laughing so much.
Hilary and Roger discuss technical topics that may, at a glance seem too dry for a pod cast, but they always manage to keep it interesting and light hearted. I learn something new every episode. Keep up the good work!
The contents are somewhat interesting, but they look like teenagers talking.
My favorite data science podcast. I always listen.
It's so annoying to hear the female host laughs for no reason and just keep laughing every sentence she says. I wish you could edit out all the laughs.
Somehow funny, engaging, and smart...even to this non-data scientist. Keep up the good work.
... listen to this. If you simply want to pass away the day with meandering discussions, this is your podcast. Yes, there is some very interesting stuff sprinkeld in, but the cost of finding the good parts is too high. If you love listening to academics whining about the real world, this is for you too!
Podcast has some potential given the content but like other reviewers, I had to stop listening and unsubscribe because of the verbal fillers. One of the hosts uses "like" excessively and it makes the podcast impossible to listen to.
I have to think Hilary is smart but why does she laugh at everything she says. Is every sentence is a joke, sarcastic maybe or is she nervous? I want to listen because I like the fun of the show but she says something smart and than laughs. I though she would listen through some of what they record, hear this and try to but back. Fun shows where they laugh about funny things are great, joking around makes advanced topic like this more fun but laughing at your own words is a bummer.
I came to this podcast through Peng's coursera material, but Hilary's "like"s and giggle and overall haphazard way of speaking really distracts from her insights and contributions. Please please please fix this by using fewer verbal fillers and having more concrete sentences and ideas. Otherwise, content is great once you can sift through the giggles and like and the such.
Great podcast! Fascinating discussions on stats, data and various related topics. A helpful intro for someone new to the field. The blend of the industry and academic perspective works well. Keep up the good work!
I always want to try and like this podcast, but it's way too rambly. You rarely seem to stay on topic like more professional podcasts. It's also very clique-y and filled name dropping. Do I know who David Robinson is? Sure, but that's because I travel as the same twitter circles as Roger and Hilary. When I do listen to your podcast I have to skip around to get to the meat of the conversation. The irony is you even joke about how bad it is relative to the other better data science podcasts out there. Why not try and improve?
Lively banter. Good stuff from a couple pros. Not as much profanity as "My Favorite Murder." Linked to #RCatLadies
I've loved this podcast since the beginning for it's sense of fun and whimsy in the deep world of data science. It makes some really fundamental concepts accessible and provides a lot of food for thought. Heck, I enjoy it so much I give my students extra credit if they talk about it in class. Although no one has jumped on this...yet...
This used to be one of my favorite podcasts but every week it feels like they are struggling to find topics to talk about.Recommendation 1: Look at what others are talking about during their data science podcastsRecommendation 2: Bring more speakers to talk. You guys are sitting in between Academia and Professional life and it should be easier for you to find speakers than anyone else.
Hilary and Roger operate my favorite 4.5 star data science podcast. And it's not even close!
I enjoyed the back and forth in episode nine on the problems with spreadsheet based analysis and the very real reasons their not going anywhere anytime soon.
Love the podcast. Thanks for all you put into it!
I just re-listened to your guy's first episode. It was so good! You guys were really on that day lol. Keep up the conversation and don't ever go away!
I really appreciate having a podcast on data science. The host are mostly very knowledgable and topics are of great interest. However, I agree with a number of reviewers. One host uses "yeah" way too much. Listening to episode 16 on my 15 minute commute I counted 39 "yeahs". A number of sentences are started with, "Yeah, yeah..." I say this as constructive criticism. Podcasting is not like a conversation as mentioned, in defense, in another view. I hope the host do take this as constructive criticism and implement change. If they did, I would give a 5 star.
I listen to this podcast on a sporadic basis. I've found some of the episodes more interesting an useful than others. Yes, some of the episodes are a bit too giddy, giggly. In general the material is practical. Some of it is career-oriented and therefore of potential interest to students in business, data science, etc.
This podcast was unlistenable given how many times the girl says "like"So frustrating
Listening to Roger and Hillary kibitz about their methods and their world is like McPartland talking to old Jazz pros about gigs, licks, styles, personalities â the practice of making music. Itâs really fun!
As Iâm making the transition from academia to the âreal worldâ I love this insiderâs view on the contrast between these arenas. The content of the podcast naturally flows from serious stats issues to the culture and metaconversations of the field, to the trivial. What I like most is that itâs just two super smart people chatting without an agenda other than to pick each otherâs brains and have fun. Their enthusiasm is definitely contagious. One of the things that makes it so successful is the contrast between the speakers: Roger comes across as a low-key experienced academic and Hilary as a creative data scientist in industry with a unique big picture perspective on how cutting edge stats can be applied to real world problems.
Great conversations about relevant news, tools and gossip in data science and statistics with special love for R. Keep it coming guys!
This is one of my favorite podcasts. It certainly makes me laugh out loud every episode, and has triggered some very interesting discussions online, as well as inspired some of my academic writing. I am acquainted with Roger and Hilary personally, and the best/worst thing about the podcast is it makes me feel like we are all BFFs. Obviously, we are not. But after eavesdropping on their conversation for an hour every couple weeks, I could be forgiven for my mistake.
I love this podcast! The format was a little odd to me at first, took me an episode or two of getting used to just enjoying the conversation instead of digging for a more traditional âstoryâ narrative, but once I did I was hooked and now I love the format. I find it creative and thought provoking. As for the commenters on the excessive use of âlikeâ by both Drs or any criticism that the hostessesâ voice isnât appropriate for a podcast - the former might be valid for a more traditional format of podcast, but the latter is NOT constructive commentary. The podcast is a recording of an informal conversation. Would you say that to someone in an in-person conversation? Or would you stop speaking or listening to her? I seriously doubt it. That line of commentary is very likely just thinly veiled sexism, possibly unconscious. Personally I find it really encouraging to hear accomplished statisticians talk in such an accessible way.
After listening to the first couple episodes, I really wanted to hear more from Dr. Peng and much less from Dr. Parker...He contributes a lot more to the podcast with regards to content.
I started taking the Data Science courses from Coursera, and then I found this podcast. You get to hear what it would be like to sit in a lounge with data scientists, one being the instructor, and listen in on how they discuss that world. It gives a great view on what it's like in data science, and let's you feel less like an outsider to the field as you're just getting started. Tons of mentions for great links, talks, papers, all given in a conversational way, that gets you immersed rather quickly. Listen to this podcast before you decide whether the field of data science is out of reach.
Great show â I feel the informal conversations are deep in content and full of insight. You guys probably need to talk a bit louder or close to the mic, and Hillary needs to talk less like a teenager (forget yaaaahs, like etc.). But you guys are great. Seriously.
I "like" this podcast but I do agree that there the use of "like" can be annoying. Granted it is new for them so I hope we have not seen the best yet. Really enjoyed the episode which featured Jenny Bryan. They should make her regular on this podcast.
My favorite way to learn about a field is to hear experts talk about it in passing, so this podcast is one of my favorite to listen to :)
Hi, I enjoy the podcast but the audio quality is not as high as other podcasts. The volume is also relatively low in comparison to other podcasts. Easy to hear when surrounding is quiet but hard to hear when running or on train.
Great podcast to listen to different takes on data analysis. I hope the podcast continues to evolve as I've really enjoyed the topics, the informal structure, and the new inclusion of guests.
I really appreciate your guys banter. Thought I needed to give Hilary some love because there are a couple of mean reviews on her. Be compassionate people, she's a data scientist not an entertainer.
The content in this podcast is interesting and I really really want to learn more and keep listening!BUTHilary says "like" far too excessively. So I noticed Roger saying it as well. I couldn't finish the episode as a result. Discourse markers such as "so", "right", "well", "anyway" and "like" certainly have their place in our normal conversation. However, using them excessively to fill gaps while you process what to say next is unacceptable for listeners of a podcast. Best tip for the future? Slow down. You guys are intelligent and you have really interesting stuff to say that we all want to hear.Thanks for taking my suggestions into consideration!
Yeah, so I like really wanted to like this cuz I have Peng's book and I have like taken his course and yeah it'S like too bad this is so like unlistenable. For such educated people you say "Like" waaaaayyyy too much. It's intolerable. Don't you listen to yourselves? Also, Sorry but the woman's voice is not radio friendly. Above average attempt for amateur podcast in data science, but the first time I've been unable to stand the speech to such an extent I've had to turn it off. I had to write this negative review in hopes the hosts will edit themselves better, and like talk like Ph.D.s. like should.Like.
I really enjoy the podcasts. As a student in the Coursera Data Science certificate, I am looking to learn as much about the field as possible. I am finding the informal discussions about the field very informative. They keep the discussion light and fun while still discussing relevant issues in the field. I hope there are many more podcasts to come.
Iâm in a MS program in biostats currently, and this is one of the coolest things Iâve ever listened to. As a student, itâs so cool to listen to two professionals speak about the field in an informal way. Really enjoyed the 3rd episode :)
Interesting, informative, entertaining, thoughtful discussion and perspective on R and statistics from two experts with academic and applied backgrounds.